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"Identifying feature types": [[131, "Identifying-feature-types"], [132, "Identifying-feature-types"], [135, "Identifying-feature-types"]], "Creating data preprocessors": [[131, "Creating-data-preprocessors"], [132, "Creating-data-preprocessors"], [135, "Creating-data-preprocessors"]], "Creating Hugging Face Dataset": [[131, "Creating-Hugging-Face-Dataset"], [132, "Creating-Hugging-Face-Dataset"], [135, "Creating-Hugging-Face-Dataset"]], "Model Creation": [[131, "Model-Creation"], [132, "Model-Creation"], [133, "Model-Creation"], [135, "Model-Creation"]], "Task Creation": [[131, "Task-Creation"], [132, "Task-Creation"], [135, "Task-Creation"]], "Training": [[131, "Training"], [132, "Training"], [135, "Training"]], "Prediction": [[131, "Prediction"], [132, "Prediction"], [135, "Prediction"]], "Evaluation": [[131, "Evaluation"], [132, "Evaluation"], [135, "Evaluation"]], "Report Generation": [[131, "Report-Generation"], [132, "Report-Generation"], [135, "Report-Generation"]], "Mortality Prediction": [[132, "Mortality-Prediction"]], "Data Querying & Processing": [[132, "Data-Querying-&-Processing"]], "Compute mortality (labels)": [[132, "Compute-mortality-(labels)"]], "Data Inspection and Preprocessing": [[132, "Data-Inspection-and-Preprocessing"], [135, "Data-Inspection-and-Preprocessing"]], "Drop NaNs based on the NAN_THRESHOLD": [[132, "Drop-NaNs-based-on-the-NAN_THRESHOLD"], [135, "Drop-NaNs-based-on-the-NAN_THRESHOLD"]], "Gender distribution": [[132, "Gender-distribution"], [135, "Gender-distribution"]], "Chest X-Ray Disease Classification": [[133, "Chest-X-Ray-Disease-Classification"]], "Generate Historical Reports": [[133, "Generate-Historical-Reports"]], "Initialize Periodic Report": [[133, "Initialize-Periodic-Report"]], "Load Dataset": [[133, "Load-Dataset"]], "Multilabel AUROC by Pathology and Sex": [[133, "Multilabel-AUROC-by-Pathology-and-Sex"]], "Multilabel AUROC by Pathology and Age": [[133, "Multilabel-AUROC-by-Pathology-and-Age"]], "Log Performance Metrics as Tests w/ Thresholds": [[133, "Log-Performance-Metrics-as-Tests-w/-Thresholds"]], "Populate Model Card Fields": [[133, "Populate-Model-Card-Fields"]], "NIHCXR Clinical Drift Experiments Tutorial": [[134, "NIHCXR-Clinical-Drift-Experiments-Tutorial"]], "Import Libraries and Load NIHCXR Dataset": [[134, "Import-Libraries-and-Load-NIHCXR-Dataset"]], "Example 1. Generate Source/Target Dataset for Experiments (1-2)": [[134, "Example-1.-Generate-Source/Target-Dataset-for-Experiments-(1-2)"]], "Example 2. Sensitivity test experiment with 3 dimensionality reduction techniques": [[134, "Example-2.-Sensitivity-test-experiment-with-3-dimensionality-reduction-techniques"]], "Example 3. Sensitivity test experiment with models trained on different datasets": [[134, "Example-3.-Sensitivity-test-experiment-with-models-trained-on-different-datasets"]], "Example 4. Sensitivity test experiment with different clinical shifts": [[134, "Example-4.-Sensitivity-test-experiment-with-different-clinical-shifts"]], "Example 5. Rolling window experiment with synthetic timestamps using biweekly window": [[134, "Example-5.-Rolling-window-experiment-with-synthetic-timestamps-using-biweekly-window"]], "Prolonged Length of Stay Prediction": [[135, "Prolonged-Length-of-Stay-Prediction"]], "Data Querying": [[135, "Data-Querying"]], "Compute length of stay (labels)": [[135, "Compute-length-of-stay-(labels)"]], "Length of stay distribution": [[135, "Length-of-stay-distribution"]], "monitor API": [[136, "monitor-api"]], "Example use cases": [[137, "example-use-cases"]], "Tabular data": [[137, "tabular-data"]], "Kaggle Heart Failure Prediction": [[137, "kaggle-heart-failure-prediction"]], "MIMICIV Mortality Prediction": [[137, "mimiciv-mortality-prediction"]], "Synthea Prolonged Length of Stay Prediction": [[137, "synthea-prolonged-length-of-stay-prediction"]], "Image data": [[137, "image-data"]], "NIH Chest X-ray classification": [[137, "nih-chest-x-ray-classification"]]}, "indexentries": 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"Multilabel-AUROC-by-Pathology-and-Sex"]], "Multilabel AUROC by Pathology and Age": [[133, "Multilabel-AUROC-by-Pathology-and-Age"]], "Log Performance Metrics as Tests w/ Thresholds": [[133, "Log-Performance-Metrics-as-Tests-w/-Thresholds"]], "Populate Model Card Fields": [[133, "Populate-Model-Card-Fields"]], "NIHCXR Clinical Drift Experiments Tutorial": [[134, "NIHCXR-Clinical-Drift-Experiments-Tutorial"]], "Import Libraries and Load NIHCXR Dataset": [[134, "Import-Libraries-and-Load-NIHCXR-Dataset"]], "Example 1. Generate Source/Target Dataset for Experiments (1-2)": [[134, "Example-1.-Generate-Source/Target-Dataset-for-Experiments-(1-2)"]], "Example 2. Sensitivity test experiment with 3 dimensionality reduction techniques": [[134, "Example-2.-Sensitivity-test-experiment-with-3-dimensionality-reduction-techniques"]], "Example 3. Sensitivity test experiment with models trained on different datasets": [[134, "Example-3.-Sensitivity-test-experiment-with-models-trained-on-different-datasets"]], "Example 4. Sensitivity test experiment with different clinical shifts": [[134, "Example-4.-Sensitivity-test-experiment-with-different-clinical-shifts"]], "Example 5. Rolling window experiment with synthetic timestamps using biweekly window": [[134, "Example-5.-Rolling-window-experiment-with-synthetic-timestamps-using-biweekly-window"]], "Prolonged Length of Stay Prediction": [[135, "Prolonged-Length-of-Stay-Prediction"]], "Data Querying": [[135, "Data-Querying"]], "Compute length of stay (labels)": [[135, "Compute-length-of-stay-(labels)"]], "Length of stay distribution": [[135, "Length-of-stay-distribution"]], "monitor API": [[136, "monitor-api"]], "Example use cases": [[137, "example-use-cases"]], "Tabular data": [[137, "tabular-data"]], "Kaggle Heart Failure Prediction": [[137, "kaggle-heart-failure-prediction"]], "MIMICIV Mortality Prediction": [[137, "mimiciv-mortality-prediction"]], "Synthea Prolonged Length of Stay Prediction": [[137, "synthea-prolonged-length-of-stay-prediction"]], "Image data": [[137, "image-data"]], "NIH Chest X-ray classification": [[137, "nih-chest-x-ray-classification"]]}, "indexentries": 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"module-cyclops.report"]], "cyclops.tasks": [[129, "module-cyclops.tasks"]]}}) \ No newline at end of file diff --git a/api/tutorials/kaggle/heart_failure_prediction.html b/api/tutorials/kaggle/heart_failure_prediction.html index 0c0bd015c..6dd0ec79e 100644 --- a/api/tutorials/kaggle/heart_failure_prediction.html +++ b/api/tutorials/kaggle/heart_failure_prediction.html @@ -549,7 +549,7 @@

Data Loading 
-2023-12-19 14:21:35,255 INFO cyclops.utils.file - Loading DataFrame from ./data/heart.csv
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Sex values

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Training 
-2023-12-19 14:21:42,718 INFO cyclops.models.wrappers.sk_model - Best alpha: 0.001
-2023-12-19 14:21:42,719 INFO cyclops.models.wrappers.sk_model - Best eta0: 0.01
-2023-12-19 14:21:42,720 INFO cyclops.models.wrappers.sk_model - Best learning_rate: adaptive
+2023-12-19 17:24:54,169 INFO cyclops.models.wrappers.sk_model - Best alpha: 0.001
+2023-12-19 17:24:54,170 INFO cyclops.models.wrappers.sk_model - Best eta0: 0.01
+2023-12-19 17:24:54,171 INFO cyclops.models.wrappers.sk_model - Best learning_rate: adaptive
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Prediction

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Evaluation

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[36]:
@@ -1399,25 +1399,25 @@ 
Evaluation
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Log the performance metrics to the report.

We can add a performance metric to the model card using the log_performance_metric method, which expects a dictionary where the keys are in the following format: slice_name/metric_name. For instance, overall/accuracy.

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Evaluation
-

diff --git a/api/tutorials/kaggle/heart_failure_prediction.ipynb b/api/tutorials/kaggle/heart_failure_prediction.ipynb index 51272bc15..f47a65bc6 100644 --- a/api/tutorials/kaggle/heart_failure_prediction.ipynb +++ b/api/tutorials/kaggle/heart_failure_prediction.ipynb @@ -21,10 +21,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2023-12-19T19:21:29.911924Z", - "iopub.status.busy": "2023-12-19T19:21:29.911462Z", - "iopub.status.idle": "2023-12-19T19:21:34.681585Z", - "shell.execute_reply": "2023-12-19T19:21:34.680870Z" + "iopub.execute_input": "2023-12-19T22:24:42.147742Z", + "iopub.status.busy": "2023-12-19T22:24:42.147119Z", + "iopub.status.idle": "2023-12-19T22:24:46.116463Z", + "shell.execute_reply": "2023-12-19T22:24:46.115752Z" }, "tags": [] }, @@ -83,10 +83,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2023-12-19T19:21:34.687059Z", - "iopub.status.busy": "2023-12-19T19:21:34.686624Z", - "iopub.status.idle": "2023-12-19T19:21:34.690562Z", - "shell.execute_reply": "2023-12-19T19:21:34.689900Z" + "iopub.execute_input": "2023-12-19T22:24:46.123258Z", + "iopub.status.busy": "2023-12-19T22:24:46.122748Z", + "iopub.status.idle": "2023-12-19T22:24:46.126654Z", + "shell.execute_reply": "2023-12-19T22:24:46.125892Z" } }, "outputs": [], @@ -106,10 +106,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2023-12-19T19:21:34.695981Z", - "iopub.status.busy": "2023-12-19T19:21:34.695557Z", - "iopub.status.idle": "2023-12-19T19:21:34.700235Z", - "shell.execute_reply": "2023-12-19T19:21:34.699369Z" + "iopub.execute_input": "2023-12-19T22:24:46.135438Z", + "iopub.status.busy": "2023-12-19T22:24:46.135016Z", + "iopub.status.idle": "2023-12-19T22:24:46.140266Z", + "shell.execute_reply": "2023-12-19T22:24:46.139063Z" }, "tags": [] }, @@ -135,10 +135,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2023-12-19T19:21:34.705437Z", - "iopub.status.busy": "2023-12-19T19:21:34.704931Z", - "iopub.status.idle": "2023-12-19T19:21:35.248417Z", - "shell.execute_reply": "2023-12-19T19:21:35.247130Z" + "iopub.execute_input": "2023-12-19T22:24:46.145299Z", + "iopub.status.busy": "2023-12-19T22:24:46.144783Z", + "iopub.status.idle": "2023-12-19T22:24:46.696459Z", + "shell.execute_reply": "2023-12-19T22:24:46.694977Z" }, "tags": [] }, @@ -158,10 +158,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2023-12-19T19:21:35.253934Z", - "iopub.status.busy": "2023-12-19T19:21:35.253471Z", - "iopub.status.idle": "2023-12-19T19:21:35.278541Z", - "shell.execute_reply": "2023-12-19T19:21:35.277775Z" + "iopub.execute_input": "2023-12-19T22:24:46.703963Z", + "iopub.status.busy": "2023-12-19T22:24:46.703222Z", + "iopub.status.idle": "2023-12-19T22:24:46.732327Z", + "shell.execute_reply": "2023-12-19T22:24:46.731265Z" }, "tags": [] }, @@ -170,7 +170,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2023-12-19 14:21:35,255 \u001b[1;37mINFO\u001b[0m cyclops.utils.file - Loading DataFrame from ./data/heart.csv\n" + "2023-12-19 17:24:46,706 \u001b[1;37mINFO\u001b[0m cyclops.utils.file - Loading DataFrame from ./data/heart.csv\n" ] }, { @@ -226,10 +226,10 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2023-12-19T19:21:35.309588Z", - "iopub.status.busy": "2023-12-19T19:21:35.308558Z", - "iopub.status.idle": "2023-12-19T19:21:35.969015Z", - "shell.execute_reply": "2023-12-19T19:21:35.967609Z" + "iopub.execute_input": "2023-12-19T22:24:46.765987Z", + "iopub.status.busy": "2023-12-19T22:24:46.765252Z", + "iopub.status.idle": "2023-12-19T22:24:47.270238Z", + "shell.execute_reply": "2023-12-19T22:24:47.269547Z" }, "tags": [] }, @@ -2037,9 +2037,9 @@ } }, "text/html": [ - "
+
@@ -1380,7 +1380,7 @@

Graphics

-
+
@@ -1388,7 +1388,7 @@

Graphics

-
+
@@ -1454,7 +1454,7 @@

Quantitative Analysis

- 0.96 + 1.0 @@ -1487,7 +1487,7 @@

Quantitative Analysis
- 0.73 + 1.0 @@ -1520,7 +1520,7 @@

Quantitative Analysis
- 0.89 + 0.86 @@ -1553,7 +1553,7 @@

Quantitative Analysis
- 0.91 + 1.0 @@ -1586,7 +1586,7 @@

Quantitative Analysis
- 0.99 + 1.0 @@ -1619,7 +1619,7 @@

Quantitative Analysis
- 0.73 + 1.0 @@ -1653,7 +1653,7 @@

Graphics

-
+
@@ -1661,7 +1661,7 @@

Graphics

-
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@@ -1669,7 +1669,7 @@

Graphics

-
+
@@ -1677,7 +1677,7 @@

Graphics

-
+
@@ -1731,7 +1731,7 @@

Graphics

-
+
@@ -2006,8 +2006,8 @@

Model Parameters

-

Penalty

- l2 +

Average

+ False
@@ -2015,8 +2015,8 @@

Penalty

-

Verbose

- 0 +

Power_t

+ 0.5
@@ -2024,8 +2024,8 @@

Verbose

-

Power_t

- 0.5 +

Loss

+ log_loss
@@ -2033,8 +2033,8 @@

Power_t

-

L1_ratio

- 0.15 +

Shuffle

+ True
@@ -2042,8 +2042,8 @@

L1_ratio

-

Learning_rate

- adaptive +

Penalty

+ l2
@@ -2051,8 +2051,8 @@

Learning_rate

-

Loss

- log_loss +

Early_stopping

+ True
@@ -2060,26 +2060,22 @@

Loss

-

N_iter_no_change

- 5 +

Class_weight

+ balanced
-
-

Early_stopping

- True -
-

Class_weight

- balanced +

Alpha

+ 0.001
@@ -2087,8 +2083,8 @@

Class_weight

-

Average

- False +

Validation_fraction

+ 0.1
@@ -2096,22 +2092,26 @@

Average

-

Tol

- 0.001 +

Max_iter

+ 1000
+
+

N_iter_no_change

+ 5 +
-

Fit_intercept

- True +

Random_state

+ 123
@@ -2119,8 +2119,8 @@

Fit_intercept

-

Shuffle

- True +

Warm_start

+ False
@@ -2128,8 +2128,8 @@

Shuffle

-

Random_state

- 123 +

Fit_intercept

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@@ -2137,8 +2137,8 @@

Random_state

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Alpha

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Eta0

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Alpha

-

Max_iter

- 1000 +

Tol

+ 0.001
@@ -2155,8 +2155,8 @@

Max_iter

-

Epsilon

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Learning_rate

+ adaptive
@@ -2164,8 +2164,8 @@

Epsilon

-

Validation_fraction

- 0.1 +

Verbose

+ 0
@@ -2173,8 +2173,8 @@

Validation_fraction

-

Warm_start

- False +

Epsilon

+ 0.1
@@ -2182,8 +2182,8 @@

Warm_start

-

Eta0

- 0.01 +

L1_ratio

+ 0.15
@@ -2495,7 +2495,7 @@

Ethical Considerations

function generate_model_card_plot() { var model_card_plots = [] var overall_indices = [12, 13, 14, 15, 16, 17] - var histories = JSON.parse("{\"0\": [\"0.8421052631578947\", \"0.9563183143956834\", \"0.9669304094853757\", \"0.9464206356017884\", \"0.8867207186839391\"], \"1\": [\"0.8260869565217391\", \"0.6723729263763614\", \"0.6307009706881452\", \"0.6975453037482373\", \"0.8718854015617544\"], \"2\": [\"0.6785714285714286\", \"0.5539900684594384\", \"0.7508264802360016\", \"0.8578278654205337\", \"0.8255499641300726\"], \"3\": [\"0.7450980392156863\", \"0.7737847819200602\", \"0.8007894179282308\", \"0.8551127856422635\", \"0.9472919169510678\"], \"4\": [\"0.8819444444444444\", \"0.9334174941739443\", \"1.0\", \"0.9163832993690382\", \"0.9208514687388986\"], \"5\": [\"0.7804346778900575\", \"0.7730946078115127\", \"0.6639907628355863\", \"0.5743575045311637\", \"0.727357331787272\"], \"6\": [\"0.8623853211009175\", \"0.8782361853448365\", \"0.9789927900665523\", \"0.8033962338442663\", \"0.9204887978945415\"], \"7\": [\"0.8676470588235294\", \"1.0\", \"1.0\", \"0.8703799428089805\", \"0.7867955296722748\"], \"8\": [\"0.9076923076923077\", \"0.9176269266269064\", \"0.7814350445829501\", \"0.6556630911002219\", \"0.3181271474849528\"], \"9\": [\"0.8872180451127819\", \"0.5616334428332529\", \"0.5349372372149382\", \"0.6081651503844128\", \"0.7397558210074878\"], \"10\": [\"0.927972027972028\", \"0.9503733953788889\", \"1.0\", \"0.987226998912839\", \"1.0\"], \"11\": [\"0.9437647444468813\", \"1.0\", \"0.7916882463916917\", \"0.8928903471679268\", \"0.7919602186590714\"], \"12\": [\"0.842391304347826\", \"1.0\", \"0.7763425895573902\", \"0.969321447120338\", \"0.9563738092930156\"], \"13\": [\"0.8686868686868687\", \"0.6383350557076345\", \"0.5674978018807262\", \"0.7383740785034321\", \"0.7279081747082601\"], \"14\": [\"0.8431372549019608\", \"0.9594407464861706\", \"0.9448403480690725\", \"0.8190534252675915\", \"0.8877974887200849\"], \"15\": [\"0.8557213930348259\", \"1.0\", \"0.9167123818097029\", \"0.9399820047316609\", \"0.9110434884084787\"], \"16\": [\"0.9152319464371114\", \"0.7797173013468413\", \"0.9154113293525944\", \"0.8909166249028894\", \"0.9887871886340454\"], \"17\": [\"0.9135027641916293\", \"0.9679478185090722\", \"0.7966254274046327\", \"0.765319785143711\", \"0.7336025200166187\"], \"18\": [\"0.796875\", \"0.809248096993\", \"nan\", \"0.7541655940754116\", \"0.7638014318063421\"]}"); + var histories = JSON.parse("{\"0\": [\"0.8421052631578947\", \"0.900307447264279\", \"0.873168914566397\", \"0.8795320011685173\", \"0.9032257294123694\"], \"1\": [\"0.8260869565217391\", \"0.7077958091940261\", \"0.6902484740139817\", \"0.5734164339049217\", \"0.7067621989045616\"], \"2\": [\"0.6785714285714286\", \"0.6822855603442981\", \"0.7626991801298384\", \"0.8946232809179748\", \"0.9583873959455838\"], \"3\": [\"0.7450980392156863\", \"0.7692370904141371\", \"0.7183441027729726\", \"0.7275993016529521\", \"0.798895757166463\"], \"4\": [\"0.8819444444444444\", \"0.962149259174959\", \"0.9949917131564872\", \"1.0\", \"0.8797990853842348\"], \"5\": [\"0.7804346778900575\", \"0.745879080326222\", \"0.6530836943086966\", \"0.6555100898340133\", \"0.7757674928293556\"], \"6\": [\"0.8623853211009175\", \"0.8264070205797504\", \"0.8877240991166256\", \"1.0\", \"1.0\"], \"7\": [\"0.8676470588235294\", \"0.8705552654752788\", \"0.7949560519233949\", \"0.8335770838954795\", \"0.6709353677315157\"], \"8\": [\"0.9076923076923077\", \"0.9413438597822475\", \"1.0\", \"0.8446642856148739\", \"0.8145094678175515\"], \"9\": [\"0.8872180451127819\", \"0.9006659646800862\", \"0.9577821419460817\", \"1.0\", \"1.0\"], \"10\": [\"0.927972027972028\", \"0.929017957284023\", \"1.0\", \"0.9252364815216615\", \"0.8197366314025815\"], \"11\": [\"0.9437647444468813\", \"0.9767158743231521\", \"0.942866258784751\", \"1.0\", \"0.9169903858840955\"], \"12\": [\"0.842391304347826\", \"1.0\", \"1.0\", \"1.0\", \"1.0\"], \"13\": [\"0.8686868686868687\", \"0.9225936620057996\", \"0.991979311144513\", \"1.0\", \"1.0\"], \"14\": [\"0.8431372549019608\", \"0.8739184854992295\", \"0.9783753916069721\", \"0.8465988196538312\", \"0.8598846242494643\"], \"15\": [\"0.8557213930348259\", \"1.0\", \"1.0\", \"0.8805219058718354\", \"1.0\"], \"16\": [\"0.9152319464371114\", \"0.7876663246958717\", \"0.8465153559866936\", \"0.9583662036168297\", \"1.0\"], \"17\": [\"0.9135027641916293\", \"0.9488557041308288\", \"0.8832603486681623\", \"0.9705670375470956\", \"1.0\"], \"18\": [\"0.796875\", \"0.7052468463756425\", \"nan\", \"0.6154292306777902\", \"0.630728642186188\"]}"); var thresholds = JSON.parse("{\"0\": \"0.7\", \"1\": \"0.7\", \"2\": \"0.7\", \"3\": \"0.7\", \"4\": \"0.7\", \"5\": \"0.7\", \"6\": \"0.7\", \"7\": \"0.7\", \"8\": \"0.7\", \"9\": \"0.7\", \"10\": \"0.7\", \"11\": \"0.7\", \"12\": \"0.7\", \"13\": \"0.7\", \"14\": \"0.7\", \"15\": \"0.7\", \"16\": \"0.7\", \"17\": \"0.7\", \"18\": \"0.7\"}"); var timestamps = JSON.parse("{\"0\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"1\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"2\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"3\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"4\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"5\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"6\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"7\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"8\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"9\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"10\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"11\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"12\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"13\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"14\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"15\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"16\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"17\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"18\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"]}"); @@ -2782,10 +2782,10 @@

Ethical Considerations

} } var slices_all = JSON.parse("{\"0\": [\"metric:Accuracy\", \"Sex:F\", \"Age:overall_Age\"], \"1\": [\"metric:Precision\", \"Age:[30 - 50)\", \"Sex:overall_Sex\"], \"2\": [\"metric:Recall\", \"Age:[30 - 50)\", \"Sex:overall_Sex\"], \"3\": [\"metric:F1 Score\", \"Age:[30 - 50)\", \"Sex:overall_Sex\"], \"4\": [\"metric:AUROC\", \"Age:[30 - 50)\", \"Sex:overall_Sex\"], \"5\": [\"metric:AveragePrecision\", \"Age:[30 - 50)\", \"Sex:overall_Sex\"], \"6\": [\"metric:Accuracy\", \"Age:[50 - 70)\", \"Sex:overall_Sex\"], \"7\": [\"metric:Precision\", \"Age:[50 - 70)\", \"Sex:overall_Sex\"], \"8\": [\"metric:Recall\", \"Age:[50 - 70)\", \"Sex:overall_Sex\"], \"9\": [\"metric:F1 Score\", \"Age:[50 - 70)\", \"Sex:overall_Sex\"], \"10\": [\"metric:AUROC\", \"Age:[50 - 70)\", \"Sex:overall_Sex\"], \"11\": [\"metric:AveragePrecision\", \"Age:[50 - 70)\", \"Sex:overall_Sex\"], \"12\": [\"metric:Accuracy\", \"Sex:overall_Sex\", \"Age:overall_Age\"], \"13\": [\"metric:Precision\", \"Sex:overall_Sex\", \"Age:overall_Age\"], \"14\": [\"metric:Recall\", \"Sex:overall_Sex\", \"Age:overall_Age\"], \"15\": [\"metric:F1 Score\", \"Sex:overall_Sex\", \"Age:overall_Age\"], \"16\": [\"metric:AUROC\", \"Sex:overall_Sex\", \"Age:overall_Age\"], \"17\": [\"metric:AveragePrecision\", \"Sex:overall_Sex\", \"Age:overall_Age\"], \"18\": [\"metric:Accuracy\", \"Age:[30 - 50)\", \"Sex:overall_Sex\"]}"); - var histories_all = JSON.parse("{\"0\": [\"0.8421052631578947\", \"0.9563183143956834\", \"0.9669304094853757\", \"0.9464206356017884\", \"0.8867207186839391\"], \"1\": [\"0.8260869565217391\", \"0.6723729263763614\", \"0.6307009706881452\", \"0.6975453037482373\", \"0.8718854015617544\"], \"2\": [\"0.6785714285714286\", \"0.5539900684594384\", \"0.7508264802360016\", \"0.8578278654205337\", \"0.8255499641300726\"], \"3\": [\"0.7450980392156863\", \"0.7737847819200602\", \"0.8007894179282308\", \"0.8551127856422635\", \"0.9472919169510678\"], \"4\": [\"0.8819444444444444\", \"0.9334174941739443\", \"1.0\", \"0.9163832993690382\", \"0.9208514687388986\"], \"5\": [\"0.7804346778900575\", \"0.7730946078115127\", \"0.6639907628355863\", \"0.5743575045311637\", \"0.727357331787272\"], \"6\": [\"0.8623853211009175\", \"0.8782361853448365\", \"0.9789927900665523\", \"0.8033962338442663\", \"0.9204887978945415\"], \"7\": [\"0.8676470588235294\", \"1.0\", \"1.0\", \"0.8703799428089805\", \"0.7867955296722748\"], \"8\": [\"0.9076923076923077\", \"0.9176269266269064\", \"0.7814350445829501\", \"0.6556630911002219\", \"0.3181271474849528\"], \"9\": [\"0.8872180451127819\", \"0.5616334428332529\", \"0.5349372372149382\", \"0.6081651503844128\", \"0.7397558210074878\"], \"10\": [\"0.927972027972028\", \"0.9503733953788889\", \"1.0\", \"0.987226998912839\", \"1.0\"], \"11\": [\"0.9437647444468813\", \"1.0\", \"0.7916882463916917\", \"0.8928903471679268\", \"0.7919602186590714\"], \"12\": [\"0.842391304347826\", \"1.0\", \"0.7763425895573902\", \"0.969321447120338\", \"0.9563738092930156\"], \"13\": [\"0.8686868686868687\", \"0.6383350557076345\", \"0.5674978018807262\", \"0.7383740785034321\", \"0.7279081747082601\"], \"14\": [\"0.8431372549019608\", \"0.9594407464861706\", \"0.9448403480690725\", \"0.8190534252675915\", \"0.8877974887200849\"], \"15\": [\"0.8557213930348259\", \"1.0\", \"0.9167123818097029\", \"0.9399820047316609\", \"0.9110434884084787\"], \"16\": [\"0.9152319464371114\", \"0.7797173013468413\", \"0.9154113293525944\", \"0.8909166249028894\", \"0.9887871886340454\"], \"17\": [\"0.9135027641916293\", \"0.9679478185090722\", \"0.7966254274046327\", \"0.765319785143711\", \"0.7336025200166187\"], \"18\": [\"0.796875\", \"0.809248096993\", \"nan\", \"0.7541655940754116\", \"0.7638014318063421\"]}"); + var histories_all = JSON.parse("{\"0\": [\"0.8421052631578947\", \"0.900307447264279\", \"0.873168914566397\", \"0.8795320011685173\", \"0.9032257294123694\"], \"1\": [\"0.8260869565217391\", \"0.7077958091940261\", \"0.6902484740139817\", \"0.5734164339049217\", \"0.7067621989045616\"], \"2\": [\"0.6785714285714286\", \"0.6822855603442981\", \"0.7626991801298384\", \"0.8946232809179748\", \"0.9583873959455838\"], \"3\": [\"0.7450980392156863\", \"0.7692370904141371\", \"0.7183441027729726\", \"0.7275993016529521\", \"0.798895757166463\"], \"4\": [\"0.8819444444444444\", \"0.962149259174959\", \"0.9949917131564872\", \"1.0\", \"0.8797990853842348\"], \"5\": [\"0.7804346778900575\", \"0.745879080326222\", \"0.6530836943086966\", \"0.6555100898340133\", \"0.7757674928293556\"], \"6\": [\"0.8623853211009175\", \"0.8264070205797504\", \"0.8877240991166256\", \"1.0\", \"1.0\"], \"7\": [\"0.8676470588235294\", \"0.8705552654752788\", \"0.7949560519233949\", \"0.8335770838954795\", \"0.6709353677315157\"], \"8\": [\"0.9076923076923077\", \"0.9413438597822475\", \"1.0\", \"0.8446642856148739\", \"0.8145094678175515\"], \"9\": [\"0.8872180451127819\", \"0.9006659646800862\", \"0.9577821419460817\", \"1.0\", \"1.0\"], \"10\": [\"0.927972027972028\", \"0.929017957284023\", \"1.0\", \"0.9252364815216615\", \"0.8197366314025815\"], \"11\": [\"0.9437647444468813\", \"0.9767158743231521\", \"0.942866258784751\", \"1.0\", \"0.9169903858840955\"], \"12\": [\"0.842391304347826\", \"1.0\", \"1.0\", \"1.0\", \"1.0\"], \"13\": [\"0.8686868686868687\", \"0.9225936620057996\", \"0.991979311144513\", \"1.0\", \"1.0\"], \"14\": [\"0.8431372549019608\", \"0.8739184854992295\", \"0.9783753916069721\", \"0.8465988196538312\", \"0.8598846242494643\"], \"15\": [\"0.8557213930348259\", \"1.0\", \"1.0\", \"0.8805219058718354\", \"1.0\"], \"16\": [\"0.9152319464371114\", \"0.7876663246958717\", \"0.8465153559866936\", \"0.9583662036168297\", \"1.0\"], \"17\": [\"0.9135027641916293\", \"0.9488557041308288\", \"0.8832603486681623\", \"0.9705670375470956\", \"1.0\"], \"18\": [\"0.796875\", \"0.7052468463756425\", \"nan\", \"0.6154292306777902\", \"0.630728642186188\"]}"); var thresholds_all = JSON.parse("{\"0\": \"0.7\", \"1\": \"0.7\", \"2\": \"0.7\", \"3\": \"0.7\", \"4\": \"0.7\", \"5\": \"0.7\", \"6\": \"0.7\", \"7\": \"0.7\", \"8\": \"0.7\", \"9\": \"0.7\", \"10\": \"0.7\", \"11\": \"0.7\", \"12\": \"0.7\", \"13\": \"0.7\", \"14\": \"0.7\", \"15\": \"0.7\", \"16\": \"0.7\", \"17\": \"0.7\", \"18\": \"0.7\"}"); - var trends_all = JSON.parse("{\"0\": \"neutral\", \"1\": \"positive\", \"2\": \"positive\", \"3\": \"positive\", \"4\": \"neutral\", \"5\": \"negative\", \"6\": \"neutral\", \"7\": \"negative\", \"8\": \"negative\", \"9\": \"negative\", \"10\": \"positive\", \"11\": \"negative\", \"12\": \"positive\", \"13\": \"negative\", \"14\": \"neutral\", \"15\": \"neutral\", \"16\": \"positive\", \"17\": \"negative\", \"18\": \"neutral\"}"); - var passed_all = JSON.parse("{\"0\": true, \"1\": true, \"2\": true, \"3\": true, \"4\": true, \"5\": true, \"6\": true, \"7\": true, \"8\": false, \"9\": true, \"10\": true, \"11\": true, \"12\": true, \"13\": true, \"14\": true, \"15\": true, \"16\": true, \"17\": true, \"18\": true}"); + var trends_all = JSON.parse("{\"0\": \"positive\", \"1\": \"negative\", \"2\": \"positive\", \"3\": \"neutral\", \"4\": \"neutral\", \"5\": \"neutral\", \"6\": \"positive\", \"7\": \"negative\", \"8\": \"negative\", \"9\": \"positive\", \"10\": \"negative\", \"11\": \"neutral\", \"12\": \"positive\", \"13\": \"positive\", \"14\": \"neutral\", \"15\": \"positive\", \"16\": \"positive\", \"17\": \"positive\", \"18\": \"neutral\"}"); + var passed_all = JSON.parse("{\"0\": true, \"1\": true, \"2\": true, \"3\": true, \"4\": true, \"5\": true, \"6\": true, \"7\": false, \"8\": true, \"9\": true, \"10\": true, \"11\": true, \"12\": true, \"13\": true, \"14\": true, \"15\": true, \"16\": true, \"17\": true, \"18\": false}"); var names_all = JSON.parse("{\"0\": \"Accuracy\", \"1\": \"Precision\", \"2\": \"Recall\", \"3\": \"F1 Score\", \"4\": \"AUROC\", \"5\": \"AveragePrecision\", \"6\": \"Accuracy\", \"7\": \"Precision\", \"8\": \"Recall\", \"9\": \"F1 Score\", \"10\": \"AUROC\", \"11\": \"AveragePrecision\", \"12\": \"Accuracy\", \"13\": \"Precision\", \"14\": \"Recall\", \"15\": \"F1 Score\", \"16\": \"AUROC\", \"17\": \"AveragePrecision\", \"18\": \"Accuracy\"}"); var timestamps_all = JSON.parse("{\"0\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"1\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"2\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"3\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"4\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"5\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"6\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"7\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"8\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"9\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"10\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"11\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"12\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"13\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"14\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"15\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"16\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"17\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"18\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"]}"); @@ -3073,10 +3073,10 @@

Ethical Considerations

} } var slices_all = JSON.parse("{\"0\": [\"metric:Accuracy\", \"Sex:F\", \"Age:overall_Age\"], \"1\": [\"metric:Precision\", \"Age:[30 - 50)\", \"Sex:overall_Sex\"], \"2\": [\"metric:Recall\", \"Age:[30 - 50)\", \"Sex:overall_Sex\"], \"3\": [\"metric:F1 Score\", \"Age:[30 - 50)\", \"Sex:overall_Sex\"], \"4\": [\"metric:AUROC\", \"Age:[30 - 50)\", \"Sex:overall_Sex\"], \"5\": [\"metric:AveragePrecision\", \"Age:[30 - 50)\", \"Sex:overall_Sex\"], \"6\": [\"metric:Accuracy\", \"Age:[50 - 70)\", \"Sex:overall_Sex\"], \"7\": [\"metric:Precision\", \"Age:[50 - 70)\", \"Sex:overall_Sex\"], \"8\": [\"metric:Recall\", \"Age:[50 - 70)\", \"Sex:overall_Sex\"], \"9\": [\"metric:F1 Score\", \"Age:[50 - 70)\", \"Sex:overall_Sex\"], \"10\": [\"metric:AUROC\", \"Age:[50 - 70)\", \"Sex:overall_Sex\"], \"11\": [\"metric:AveragePrecision\", \"Age:[50 - 70)\", \"Sex:overall_Sex\"], \"12\": [\"metric:Accuracy\", \"Sex:overall_Sex\", \"Age:overall_Age\"], \"13\": [\"metric:Precision\", \"Sex:overall_Sex\", \"Age:overall_Age\"], \"14\": [\"metric:Recall\", \"Sex:overall_Sex\", \"Age:overall_Age\"], \"15\": [\"metric:F1 Score\", \"Sex:overall_Sex\", \"Age:overall_Age\"], \"16\": [\"metric:AUROC\", \"Sex:overall_Sex\", \"Age:overall_Age\"], \"17\": [\"metric:AveragePrecision\", \"Sex:overall_Sex\", \"Age:overall_Age\"], \"18\": [\"metric:Accuracy\", \"Age:[30 - 50)\", \"Sex:overall_Sex\"]}"); - var histories_all = JSON.parse("{\"0\": [\"0.8421052631578947\", \"0.9563183143956834\", \"0.9669304094853757\", \"0.9464206356017884\", \"0.8867207186839391\"], \"1\": [\"0.8260869565217391\", \"0.6723729263763614\", \"0.6307009706881452\", \"0.6975453037482373\", \"0.8718854015617544\"], \"2\": [\"0.6785714285714286\", \"0.5539900684594384\", \"0.7508264802360016\", \"0.8578278654205337\", \"0.8255499641300726\"], \"3\": [\"0.7450980392156863\", \"0.7737847819200602\", \"0.8007894179282308\", \"0.8551127856422635\", \"0.9472919169510678\"], \"4\": [\"0.8819444444444444\", \"0.9334174941739443\", \"1.0\", \"0.9163832993690382\", \"0.9208514687388986\"], \"5\": [\"0.7804346778900575\", \"0.7730946078115127\", \"0.6639907628355863\", \"0.5743575045311637\", \"0.727357331787272\"], \"6\": [\"0.8623853211009175\", \"0.8782361853448365\", \"0.9789927900665523\", \"0.8033962338442663\", \"0.9204887978945415\"], \"7\": [\"0.8676470588235294\", \"1.0\", \"1.0\", \"0.8703799428089805\", \"0.7867955296722748\"], \"8\": [\"0.9076923076923077\", \"0.9176269266269064\", \"0.7814350445829501\", \"0.6556630911002219\", \"0.3181271474849528\"], \"9\": [\"0.8872180451127819\", \"0.5616334428332529\", \"0.5349372372149382\", \"0.6081651503844128\", \"0.7397558210074878\"], \"10\": [\"0.927972027972028\", \"0.9503733953788889\", \"1.0\", \"0.987226998912839\", \"1.0\"], \"11\": [\"0.9437647444468813\", \"1.0\", \"0.7916882463916917\", \"0.8928903471679268\", \"0.7919602186590714\"], \"12\": [\"0.842391304347826\", \"1.0\", \"0.7763425895573902\", \"0.969321447120338\", \"0.9563738092930156\"], \"13\": [\"0.8686868686868687\", \"0.6383350557076345\", \"0.5674978018807262\", \"0.7383740785034321\", \"0.7279081747082601\"], \"14\": [\"0.8431372549019608\", \"0.9594407464861706\", \"0.9448403480690725\", \"0.8190534252675915\", \"0.8877974887200849\"], \"15\": [\"0.8557213930348259\", \"1.0\", \"0.9167123818097029\", \"0.9399820047316609\", \"0.9110434884084787\"], \"16\": [\"0.9152319464371114\", \"0.7797173013468413\", \"0.9154113293525944\", \"0.8909166249028894\", \"0.9887871886340454\"], \"17\": [\"0.9135027641916293\", \"0.9679478185090722\", \"0.7966254274046327\", \"0.765319785143711\", \"0.7336025200166187\"], \"18\": [\"0.796875\", \"0.809248096993\", \"nan\", \"0.7541655940754116\", \"0.7638014318063421\"]}"); + var histories_all = JSON.parse("{\"0\": [\"0.8421052631578947\", \"0.900307447264279\", \"0.873168914566397\", \"0.8795320011685173\", \"0.9032257294123694\"], \"1\": [\"0.8260869565217391\", \"0.7077958091940261\", \"0.6902484740139817\", \"0.5734164339049217\", \"0.7067621989045616\"], \"2\": [\"0.6785714285714286\", \"0.6822855603442981\", \"0.7626991801298384\", \"0.8946232809179748\", \"0.9583873959455838\"], \"3\": [\"0.7450980392156863\", \"0.7692370904141371\", \"0.7183441027729726\", \"0.7275993016529521\", \"0.798895757166463\"], \"4\": [\"0.8819444444444444\", \"0.962149259174959\", \"0.9949917131564872\", \"1.0\", \"0.8797990853842348\"], \"5\": [\"0.7804346778900575\", \"0.745879080326222\", \"0.6530836943086966\", \"0.6555100898340133\", \"0.7757674928293556\"], \"6\": [\"0.8623853211009175\", \"0.8264070205797504\", \"0.8877240991166256\", \"1.0\", \"1.0\"], \"7\": [\"0.8676470588235294\", \"0.8705552654752788\", \"0.7949560519233949\", \"0.8335770838954795\", \"0.6709353677315157\"], \"8\": [\"0.9076923076923077\", \"0.9413438597822475\", \"1.0\", \"0.8446642856148739\", \"0.8145094678175515\"], \"9\": [\"0.8872180451127819\", \"0.9006659646800862\", \"0.9577821419460817\", \"1.0\", \"1.0\"], \"10\": [\"0.927972027972028\", \"0.929017957284023\", \"1.0\", \"0.9252364815216615\", \"0.8197366314025815\"], \"11\": [\"0.9437647444468813\", \"0.9767158743231521\", \"0.942866258784751\", \"1.0\", \"0.9169903858840955\"], \"12\": [\"0.842391304347826\", \"1.0\", \"1.0\", \"1.0\", \"1.0\"], \"13\": [\"0.8686868686868687\", \"0.9225936620057996\", \"0.991979311144513\", \"1.0\", \"1.0\"], \"14\": [\"0.8431372549019608\", \"0.8739184854992295\", \"0.9783753916069721\", \"0.8465988196538312\", \"0.8598846242494643\"], \"15\": [\"0.8557213930348259\", \"1.0\", \"1.0\", \"0.8805219058718354\", \"1.0\"], \"16\": [\"0.9152319464371114\", \"0.7876663246958717\", \"0.8465153559866936\", \"0.9583662036168297\", \"1.0\"], \"17\": [\"0.9135027641916293\", \"0.9488557041308288\", \"0.8832603486681623\", \"0.9705670375470956\", \"1.0\"], \"18\": [\"0.796875\", \"0.7052468463756425\", \"nan\", \"0.6154292306777902\", \"0.630728642186188\"]}"); var thresholds_all = JSON.parse("{\"0\": \"0.7\", \"1\": \"0.7\", \"2\": \"0.7\", \"3\": \"0.7\", \"4\": \"0.7\", \"5\": \"0.7\", \"6\": \"0.7\", \"7\": \"0.7\", \"8\": \"0.7\", \"9\": \"0.7\", \"10\": \"0.7\", \"11\": \"0.7\", \"12\": \"0.7\", \"13\": \"0.7\", \"14\": \"0.7\", \"15\": \"0.7\", \"16\": \"0.7\", \"17\": \"0.7\", \"18\": \"0.7\"}"); - var trends_all = JSON.parse("{\"0\": \"neutral\", \"1\": \"positive\", \"2\": \"positive\", \"3\": \"positive\", \"4\": \"neutral\", \"5\": \"negative\", \"6\": \"neutral\", \"7\": \"negative\", \"8\": \"negative\", \"9\": \"negative\", \"10\": \"positive\", \"11\": \"negative\", \"12\": \"positive\", \"13\": \"negative\", \"14\": \"neutral\", \"15\": \"neutral\", \"16\": \"positive\", \"17\": \"negative\", \"18\": \"neutral\"}"); - var passed_all = JSON.parse("{\"0\": true, \"1\": true, \"2\": true, \"3\": true, \"4\": true, \"5\": true, \"6\": true, \"7\": true, \"8\": false, \"9\": true, \"10\": true, \"11\": true, \"12\": true, \"13\": true, \"14\": true, \"15\": true, \"16\": true, \"17\": true, \"18\": true}"); + var trends_all = JSON.parse("{\"0\": \"positive\", \"1\": \"negative\", \"2\": \"positive\", \"3\": \"neutral\", \"4\": \"neutral\", \"5\": \"neutral\", \"6\": \"positive\", \"7\": \"negative\", \"8\": \"negative\", \"9\": \"positive\", \"10\": \"negative\", \"11\": \"neutral\", \"12\": \"positive\", \"13\": \"positive\", \"14\": \"neutral\", \"15\": \"positive\", \"16\": \"positive\", \"17\": \"positive\", \"18\": \"neutral\"}"); + var passed_all = JSON.parse("{\"0\": true, \"1\": true, \"2\": true, \"3\": true, \"4\": true, \"5\": true, \"6\": true, \"7\": false, \"8\": true, \"9\": true, \"10\": true, \"11\": true, \"12\": true, \"13\": true, \"14\": true, \"15\": true, \"16\": true, \"17\": true, \"18\": false}"); var names_all = JSON.parse("{\"0\": \"Accuracy\", \"1\": \"Precision\", \"2\": \"Recall\", \"3\": \"F1 Score\", \"4\": \"AUROC\", \"5\": \"AveragePrecision\", \"6\": \"Accuracy\", \"7\": \"Precision\", \"8\": \"Recall\", \"9\": \"F1 Score\", \"10\": \"AUROC\", \"11\": \"AveragePrecision\", \"12\": \"Accuracy\", \"13\": \"Precision\", \"14\": \"Recall\", \"15\": \"F1 Score\", \"16\": \"AUROC\", \"17\": \"AveragePrecision\", \"18\": \"Accuracy\"}"); var timestamps_all = JSON.parse("{\"0\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"1\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"2\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"3\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"4\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"5\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"6\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"7\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"8\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"9\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"10\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"11\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"12\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"13\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"14\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"15\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"16\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"17\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"], \"18\": [\"2021-09-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\", \"2022-02-01\"]}"); diff --git a/api/tutorials/mimiciv/mortality_prediction.html b/api/tutorials/mimiciv/mortality_prediction.html index d61e586b3..04daeedb9 100644 --- a/api/tutorials/mimiciv/mortality_prediction.html +++ b/api/tutorials/mimiciv/mortality_prediction.html @@ -709,9 +709,9 @@

Compute mortality (labels) 
-2023-12-19 14:21:56,894 INFO cycquery.orm    - Database setup, ready to run queries!
-2023-12-19 14:22:04,394 INFO cycquery.orm    - Query returned successfully!
-2023-12-19 14:22:04,395 INFO cycquery.utils.profile - Finished executing function run_query in 5.323046 s
+2023-12-19 17:25:06,958 INFO cycquery.orm    - Database setup, ready to run queries!
+2023-12-19 17:25:14,476 INFO cycquery.orm    - Query returned successfully!
+2023-12-19 17:25:14,477 INFO cycquery.utils.profile - Finished executing function run_query in 5.304767 s

@@ -730,8 +730,8 @@

Compute mortality (labels) 
-2023-12-19 14:22:39,760 INFO cycquery.orm    - Query returned successfully!
-2023-12-19 14:22:39,761 INFO cycquery.utils.profile - Finished executing function run_query in 34.596603 s
+2023-12-19 17:25:36,285 INFO cycquery.orm    - Query returned successfully!
+2023-12-19 17:25:36,286 INFO cycquery.utils.profile - Finished executing function run_query in 21.061094 s

@@ -796,9 +796,9 @@

Drop NaNs based on the

-
+
@@ -1276,12 +1276,12 @@

Training 

-2023-12-19 14:25:18,784 INFO cyclops.models.wrappers.sk_model - Best reg_lambda: 1
-2023-12-19 14:25:18,785 INFO cyclops.models.wrappers.sk_model - Best n_estimators: 500
-2023-12-19 14:25:18,786 INFO cyclops.models.wrappers.sk_model - Best max_depth: 5
-2023-12-19 14:25:18,786 INFO cyclops.models.wrappers.sk_model - Best learning_rate: 0.01
-2023-12-19 14:25:18,786 INFO cyclops.models.wrappers.sk_model - Best gamma: 1
-2023-12-19 14:25:18,787 INFO cyclops.models.wrappers.sk_model - Best colsample_bytree: 0.8
+2023-12-19 17:28:21,122 INFO cyclops.models.wrappers.sk_model - Best reg_lambda: 1
+2023-12-19 17:28:21,123 INFO cyclops.models.wrappers.sk_model - Best n_estimators: 250
+2023-12-19 17:28:21,123 INFO cyclops.models.wrappers.sk_model - Best max_depth: 5
+2023-12-19 17:28:21,124 INFO cyclops.models.wrappers.sk_model - Best learning_rate: 0.1
+2023-12-19 17:28:21,124 INFO cyclops.models.wrappers.sk_model - Best gamma: 10
+2023-12-19 17:28:21,124 INFO cyclops.models.wrappers.sk_model - Best colsample_bytree: 0.8
@@ -1293,22 +1293,22 @@

Training colsample_bylevel=None, colsample_bynode=None, colsample_bytree=0.8, early_stopping_rounds=None, enable_categorical=False, eval_metric='logloss', - feature_types=None, gamma=1, gpu_id=None, grow_policy=None, + feature_types=None, gamma=10, gpu_id=None, grow_policy=None, importance_type=None, interaction_constraints=None, - learning_rate=0.01, max_bin=None, max_cat_threshold=None, + learning_rate=0.1, max_bin=None, max_cat_threshold=None, max_cat_to_onehot=None, max_delta_step=None, max_depth=5, max_leaves=None, min_child_weight=3, missing=nan, - monotone_constraints=None, n_estimators=500, n_jobs=None, + monotone_constraints=None, n_estimators=250, n_jobs=None, num_parallel_tree=None, predictor=None, random_state=123, ...)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.

@@ -1325,7 +1325,7 @@

Training 

-{'objective': 'binary:logistic', 'use_label_encoder': None, 'base_score': None, 'booster': None, 'callbacks': None, 'colsample_bylevel': None, 'colsample_bynode': None, 'colsample_bytree': 0.8, 'early_stopping_rounds': None, 'enable_categorical': False, 'eval_metric': 'logloss', 'feature_types': None, 'gamma': 1, 'gpu_id': None, 'grow_policy': None, 'importance_type': None, 'interaction_constraints': None, 'learning_rate': 0.01, 'max_bin': None, 'max_cat_threshold': None, 'max_cat_to_onehot': None, 'max_delta_step': None, 'max_depth': 5, 'max_leaves': None, 'min_child_weight': 3, 'missing': nan, 'monotone_constraints': None, 'n_estimators': 500, 'n_jobs': None, 'num_parallel_tree': None, 'predictor': None, 'random_state': 123, 'reg_alpha': None, 'reg_lambda': 1, 'sampling_method': None, 'scale_pos_weight': None, 'subsample': None, 'tree_method': None, 'validate_parameters': None, 'verbosity': None, 'seed': 123}
+{'objective': 'binary:logistic', 'use_label_encoder': None, 'base_score': None, 'booster': None, 'callbacks': None, 'colsample_bylevel': None, 'colsample_bynode': None, 'colsample_bytree': 0.8, 'early_stopping_rounds': None, 'enable_categorical': False, 'eval_metric': 'logloss', 'feature_types': None, 'gamma': 10, 'gpu_id': None, 'grow_policy': None, 'importance_type': None, 'interaction_constraints': None, 'learning_rate': 0.1, 'max_bin': None, 'max_cat_threshold': None, 'max_cat_to_onehot': None, 'max_delta_step': None, 'max_depth': 5, 'max_leaves': None, 'min_child_weight': 3, 'missing': nan, 'monotone_constraints': None, 'n_estimators': 250, 'n_jobs': None, 'num_parallel_tree': None, 'predictor': None, 'random_state': 123, 'reg_alpha': None, 'reg_lambda': 1, 'sampling_method': None, 'scale_pos_weight': None, 'subsample': None, 'tree_method': None, 'validate_parameters': None, 'verbosity': None, 'seed': 123}

Log the model parameters to the report.

@@ -1361,7 +1361,7 @@

Prediction
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Evaluation

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Log the performance metrics to the report.

We can add a performance metric to the model card using the log_performance_metric method, which expects a dictionary where the keys are in the following format: slice_name/metric_name. For instance, overall/accuracy.

@@ -1694,9 +1694,9 @@

Evaluation
-
diff --git a/api/tutorials/mimiciv/mortality_prediction.ipynb b/api/tutorials/mimiciv/mortality_prediction.ipynb index 663dace75..57387fdec 100644 --- a/api/tutorials/mimiciv/mortality_prediction.ipynb +++ b/api/tutorials/mimiciv/mortality_prediction.ipynb @@ -21,10 +21,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2023-12-19T19:21:50.191850Z", - "iopub.status.busy": "2023-12-19T19:21:50.191231Z", - "iopub.status.idle": "2023-12-19T19:21:54.698991Z", - "shell.execute_reply": "2023-12-19T19:21:54.698172Z" + "iopub.execute_input": "2023-12-19T22:25:00.599216Z", + "iopub.status.busy": "2023-12-19T22:25:00.598377Z", + "iopub.status.idle": "2023-12-19T22:25:04.660406Z", + "shell.execute_reply": "2023-12-19T22:25:04.659652Z" } }, "outputs": [], @@ -88,10 +88,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2023-12-19T19:21:54.703781Z", - "iopub.status.busy": "2023-12-19T19:21:54.703214Z", - "iopub.status.idle": "2023-12-19T19:21:54.707043Z", - "shell.execute_reply": "2023-12-19T19:21:54.706424Z" + "iopub.execute_input": "2023-12-19T22:25:04.665845Z", + "iopub.status.busy": "2023-12-19T22:25:04.665476Z", + "iopub.status.idle": "2023-12-19T22:25:04.670836Z", + "shell.execute_reply": "2023-12-19T22:25:04.669360Z" } }, "outputs": [], @@ -111,10 +111,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2023-12-19T19:21:54.712155Z", - "iopub.status.busy": "2023-12-19T19:21:54.711910Z", - "iopub.status.idle": "2023-12-19T19:21:54.715342Z", - "shell.execute_reply": "2023-12-19T19:21:54.714679Z" + "iopub.execute_input": "2023-12-19T22:25:04.676795Z", + "iopub.status.busy": "2023-12-19T22:25:04.675948Z", + "iopub.status.idle": "2023-12-19T22:25:04.682409Z", + "shell.execute_reply": "2023-12-19T22:25:04.681173Z" } }, "outputs": [], @@ -146,10 +146,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2023-12-19T19:21:54.721532Z", - "iopub.status.busy": "2023-12-19T19:21:54.720727Z", - "iopub.status.idle": "2023-12-19T19:23:57.471516Z", - "shell.execute_reply": "2023-12-19T19:23:57.470350Z" + "iopub.execute_input": "2023-12-19T22:25:04.688359Z", + "iopub.status.busy": "2023-12-19T22:25:04.687799Z", + "iopub.status.idle": "2023-12-19T22:26:22.496195Z", + "shell.execute_reply": "2023-12-19T22:26:22.460203Z" } }, "outputs": [ @@ -157,21 +157,21 @@ "name": "stderr", "output_type": "stream", "text": [ - "2023-12-19 14:21:56,894 \u001b[1;37mINFO\u001b[0m cycquery.orm - Database setup, ready to run queries!\n" + "2023-12-19 17:25:06,958 \u001b[1;37mINFO\u001b[0m cycquery.orm - Database setup, ready to run queries!\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2023-12-19 14:22:04,394 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" + "2023-12-19 17:25:14,476 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2023-12-19 14:22:04,395 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 5.323046 s\n" + "2023-12-19 17:25:14,477 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 5.304767 s\n" ] }, { @@ -188,14 +188,14 @@ "name": "stderr", "output_type": "stream", "text": [ - "2023-12-19 14:22:39,760 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" + "2023-12-19 17:25:36,285 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2023-12-19 14:22:39,761 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 34.596603 s\n" + "2023-12-19 17:25:36,286 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 21.061094 s\n" ] }, { @@ -393,10 +393,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2023-12-19T19:23:57.477214Z", - "iopub.status.busy": "2023-12-19T19:23:57.476882Z", - "iopub.status.idle": "2023-12-19T19:23:57.647031Z", - "shell.execute_reply": "2023-12-19T19:23:57.646160Z" + "iopub.execute_input": "2023-12-19T22:26:22.512666Z", + "iopub.status.busy": "2023-12-19T22:26:22.512318Z", + "iopub.status.idle": "2023-12-19T22:26:22.674475Z", + "shell.execute_reply": "2023-12-19T22:26:22.673817Z" } }, "outputs": [ @@ -2394,9 +2394,9 @@ } }, "text/html": [ - "
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Quantitative Analysis

- 0.8 + 0.84 @@ -1192,7 +1192,7 @@

Quantitative Analysis
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Quantitative Analysis
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Quantitative Analysis
- 0.18 + 0.11 @@ -1291,7 +1291,7 @@

Quantitative Analysis
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Quantitative Analysis
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Graphics

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@@ -2240,7 +2240,7 @@

Ethical Considerations

function generate_model_card_plot() { var model_card_plots = [] var overall_indices = [24, 25, 26, 27, 28, 29] - var histories = JSON.parse("{\"0\": [\"0.9881305637982196\", \"0.9846642424596361\", \"1.0\", \"0.9774150023005145\", \"1.0\"], \"1\": [\"0.16666666666666666\", \"0.12355993933932125\", \"0.0869232309681681\", \"0.16848545439520507\", \"0.2112634461547963\"], \"2\": [\"0.25\", \"0.2830041880864144\", \"0.41993045475460566\", \"0.43225179380317375\", \"0.5597221796411271\"], \"3\": [\"0.2\", \"0.14449726458815493\", \"0.22421798595769948\", \"0.14629213269349095\", \"0.05247796386824151\"], \"4\": [\"0.8048507462686567\", \"0.9342565165150828\", \"0.8326477184475645\", \"0.7837802923586923\", \"0.6153230961656271\"], \"5\": [\"0.33532536520584333\", \"0.4483547925594397\", \"0.583228952457814\", \"0.6933369218991075\", \"0.629190295280195\"], \"6\": [\"0.9434889434889435\", \"1.0\", \"1.0\", \"0.8488761897437797\", \"0.6994719852432872\"], \"7\": [\"0.1276595744680851\", \"0.12665371341896167\", \"0.10203420425805942\", \"0.18930572267029583\", \"0.19195177972424882\"], \"8\": [\"0.5454545454545454\", \"0.4875310216838917\", \"0.3320599333256127\", \"0.22307578639712178\", \"0.15317291426986096\"], \"9\": [\"0.20689655172413793\", \"0.20145989190511068\", \"0.2731344575033684\", \"0.1656436918849981\", \"0.19540560065803958\"], \"10\": [\"0.8674855654930375\", \"0.8972268034820535\", \"0.8892416445616308\", \"0.9586238683364244\", \"1.0\"], \"11\": [\"0.24891113213186\", \"0.1575636032394537\", \"0.3054230944545963\", \"0.3397461998845977\", \"0.338375308267361\"], \"12\": [\"0.9312130177514792\", \"0.9841155604894851\", \"1.0\", \"0.962039493055335\", \"0.8425878782852144\"], \"13\": [\"0.15294117647058825\", \"0.20859391120752838\", \"0.14341995448654027\", \"0.0898049900674727\", \"0.35021070503266927\"], \"14\": [\"0.38235294117647056\", \"0.4096407769458771\", \"0.46890653428540685\", \"0.5100196064614011\", \"0.6633640244378706\"], \"15\": [\"0.2184873949579832\", \"0.1329796793667143\", \"0.16945647320999394\", \"0.29799798314722303\", \"0.2689648561382229\"], \"16\": [\"0.830335624386325\", \"0.9704158695441639\", \"0.9416619108258805\", \"0.8603671945292782\", \"0.8819785988838736\"], \"17\": [\"0.21237283774963328\", \"0.1818051388150806\", \"0.29074966402637775\", \"0.2710695923097229\", \"0.2546698742212553\"], \"18\": [\"0.9506995336442372\", \"1.0\", \"1.0\", \"0.9357066407302105\", \"0.9992375832300644\"], \"19\": [\"0.08695652173913043\", \"0.0283564318005148\", \"0.0\", \"0.0\", \"0.0\"], \"20\": [\"0.35294117647058826\", \"0.494637462315184\", \"0.47381247301334384\", \"0.4740394992563078\", \"0.5417864174811365\"], \"21\": [\"0.13953488372093023\", \"0.030782550341716897\", \"0.06214736416791168\", \"0.13897662573700637\", \"0.14984415071322915\"], \"22\": [\"0.8393848105279849\", \"0.916293454457296\", \"0.8701754081154712\", \"0.7428676909929434\", \"0.6672561518819491\"], \"23\": [\"0.17930950065270065\", \"0.1118838751608168\", \"0.0\", \"0.10268131049750805\", \"0.14136895175804054\"], \"24\": [\"0.9414651244304241\", \"0.6587923737710815\", \"0.7220200063306562\", \"0.629975663705904\", \"0.7973801920973087\"], \"25\": [\"0.12337662337662338\", \"0.31019591821104153\", \"0.36339074711680414\", \"0.37494996097136374\", \"0.32636977298833375\"], \"26\": [\"0.37254901960784315\", \"0.4531488417238344\", \"0.6367861597663401\", \"0.7816695066949879\", \"0.6777660057428346\"], \"27\": [\"0.18536585365853658\", \"0.19641463540287019\", \"0.05131505489328392\", \"0.21948175592804067\", \"0.18392049817703468\"], \"28\": [\"0.8409644371667295\", \"0.8406569558561543\", \"0.7743035610024097\", \"0.8086166367387012\", \"0.8049443967953129\"], \"29\": [\"0.18752991294664764\", \"0.26738811163079496\", \"0.1982048978346155\", \"0.20103578588117713\", \"0.07940893288934088\"]}"); + var histories = JSON.parse("{\"0\": [\"0.9910979228486647\", \"0.9551027885687664\", \"0.9476821492397716\", \"1.0\", \"0.9029265334051461\"], \"1\": [\"0.25\", \"0.24149580817347682\", \"0.17262193517018803\", \"0.22535926073266713\", \"0.08122629647048757\"], \"2\": [\"0.25\", \"0.16161902517697557\", \"0.19317238038191537\", \"0.33106000906367167\", \"0.3428178942030108\"], \"3\": [\"0.25\", \"0.3025023221105475\", \"0.40093233033145315\", \"0.40628480390712407\", \"0.2139652239476544\"], \"4\": [\"0.8391791044776119\", \"0.7379332434324294\", \"0.6852477577575716\", \"0.754138638603504\", \"0.8703993559208607\"], \"5\": [\"0.13118961352657005\", \"0.2234672098124077\", \"0.13923300434824976\", \"0.34922819769798014\", \"0.1871597497769886\"], \"6\": [\"0.9680589680589681\", \"0.9119007184395003\", \"1.0\", \"1.0\", \"1.0\"], \"7\": [\"0.1875\", \"0.2538006437107212\", \"0.4403010484145677\", \"0.32031616408149616\", \"0.37559069492862046\"], \"8\": [\"0.4090909090909091\", \"0.43837451064398497\", \"0.5600234632560943\", \"0.5412184147272299\", \"0.4473040461357677\"], \"9\": [\"0.2571428571428571\", \"0.08387545237734079\", \"0.1627556381278868\", \"0.20030989158179216\", \"0.15299651681419382\"], \"10\": [\"0.852484999433941\", \"0.8792906522229355\", \"0.8284606379279933\", \"0.9129662152294957\", \"0.9620254405731373\"], \"11\": [\"0.32173933819025763\", \"0.3194197492378962\", \"0.36016780242689395\", \"0.38168552986513293\", \"0.12722149357683438\"], \"12\": [\"0.9563609467455622\", \"0.9953473878934656\", \"1.0\", \"1.0\", \"1.0\"], \"13\": [\"0.2222222222222222\", \"0.11860156583727859\", \"0.3917822836130673\", \"0.4233227129081373\", \"0.5288538925268242\"], \"14\": [\"0.29411764705882354\", \"0.27533582846259363\", \"0.2843500366692596\", \"0.26602849961640634\", \"0.16763191666623203\"], \"15\": [\"0.25316455696202533\", \"0.323838818797371\", \"0.303620226197352\", \"0.41046833006391265\", \"0.3845286095927599\"], \"16\": [\"0.81299651878961\", \"0.802123500698371\", \"0.9162659623437334\", \"0.9217841954948318\", \"0.9017499847161142\"], \"17\": [\"0.24706249745222636\", \"0.1401421840863098\", \"0.043331174237276615\", \"0.13896997025369956\", \"0.0\"], \"18\": [\"0.9726848767488341\", \"0.9627164745384116\", \"0.9822242727928177\", \"0.9264119939813182\", \"1.0\"], \"19\": [\"0.125\", \"0.0\", \"0.0\", \"0.09179153637213769\", \"0.03622574533982135\"], \"20\": [\"0.23529411764705882\", \"0.3247727165160673\", \"0.44073235504667096\", \"0.43667117508149916\", \"0.3225955452123267\"], \"21\": [\"0.16326530612244897\", \"0.07080023250253471\", \"0.1689355745584472\", \"0.04935180293859506\", \"0.02683047803223798\"], \"22\": [\"0.842635167274457\", \"0.94235298646717\", \"0.7742650003062747\", \"0.7723691479553396\", \"0.673949872142709\"], \"23\": [\"0.207600954098402\", \"0.27683100742807426\", \"0.20516774249402575\", \"0.217530998883252\", \"0.21703466247461362\"], \"24\": [\"0.9649491763056431\", \"0.9935535980981289\", \"0.9257441699553686\", \"0.7810581620398953\", \"0.8386891937509838\"], \"25\": [\"0.18181818181818182\", \"0.12781467306126143\", \"0.1488402472474146\", \"0.16734649474642535\", \"0.0\"], \"26\": [\"0.27450980392156865\", \"0.25434997869293496\", \"0.3290002533939981\", \"0.3854039025234891\", \"0.42586954322842646\"], \"27\": [\"0.21875\", \"0.24353068059100832\", \"0.25985287146449176\", \"0.09560137627672127\", \"0.10824119394903231\"], \"28\": [\"0.8308141243649494\", \"0.9715901949951978\", \"1.0\", \"0.9446511604371872\", \"0.9174962836932693\"], \"29\": [\"0.23163107098947502\", \"0.10732818400826394\", \"0.08121729905649898\", \"0.10179918944272683\", \"0.010462741127687983\"]}"); var thresholds = JSON.parse("{\"0\": \"0.7\", \"1\": \"0.7\", \"2\": \"0.7\", \"3\": \"0.7\", \"4\": \"0.7\", \"5\": \"0.7\", \"6\": \"0.7\", \"7\": \"0.7\", \"8\": \"0.7\", \"9\": \"0.7\", \"10\": \"0.7\", \"11\": \"0.7\", \"12\": \"0.7\", \"13\": \"0.7\", \"14\": \"0.7\", \"15\": \"0.7\", \"16\": \"0.7\", \"17\": \"0.7\", \"18\": \"0.7\", \"19\": \"0.7\", \"20\": \"0.7\", \"21\": \"0.7\", \"22\": \"0.7\", \"23\": \"0.7\", \"24\": \"0.7\", \"25\": \"0.7\", \"26\": \"0.7\", \"27\": \"0.7\", \"28\": \"0.7\", \"29\": \"0.7\"}"); var timestamps = JSON.parse("{\"0\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"1\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"2\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"3\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"4\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"5\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"6\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"7\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"8\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"9\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"10\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"11\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"12\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"13\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"14\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"15\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"16\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"17\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"18\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"19\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"20\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"21\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"22\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"23\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"24\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"25\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"26\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"27\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"28\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"29\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"]}"); @@ -2527,10 +2527,10 @@

Ethical Considerations

} } var slices_all = JSON.parse("{\"0\": [\"metric:Accuracy\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"1\": [\"metric:Precision\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"2\": [\"metric:Recall\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"3\": [\"metric:F1 Score\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"4\": [\"metric:AUROC\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"5\": [\"metric:AveragePrecision\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"6\": [\"metric:Accuracy\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"7\": [\"metric:Precision\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"8\": [\"metric:Recall\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"9\": [\"metric:F1 Score\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"10\": [\"metric:AUROC\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"11\": [\"metric:AveragePrecision\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"12\": [\"metric:Accuracy\", \"gender:M\", \"age:overall_age\"], \"13\": [\"metric:Precision\", \"gender:M\", \"age:overall_age\"], \"14\": [\"metric:Recall\", \"gender:M\", \"age:overall_age\"], \"15\": [\"metric:F1 Score\", \"gender:M\", \"age:overall_age\"], \"16\": [\"metric:AUROC\", \"gender:M\", \"age:overall_age\"], \"17\": [\"metric:AveragePrecision\", \"gender:M\", \"age:overall_age\"], \"18\": [\"metric:Accuracy\", \"gender:F\", \"age:overall_age\"], \"19\": [\"metric:Precision\", \"gender:F\", \"age:overall_age\"], \"20\": [\"metric:Recall\", \"gender:F\", \"age:overall_age\"], \"21\": [\"metric:F1 Score\", \"gender:F\", \"age:overall_age\"], \"22\": [\"metric:AUROC\", \"gender:F\", \"age:overall_age\"], \"23\": [\"metric:AveragePrecision\", \"gender:F\", \"age:overall_age\"], \"24\": [\"metric:Accuracy\", \"age:overall_age\", \"gender:overall_gender\"], \"25\": [\"metric:Precision\", \"age:overall_age\", \"gender:overall_gender\"], \"26\": [\"metric:Recall\", \"age:overall_age\", \"gender:overall_gender\"], \"27\": [\"metric:F1 Score\", \"age:overall_age\", \"gender:overall_gender\"], \"28\": [\"metric:AUROC\", \"age:overall_age\", \"gender:overall_gender\"], \"29\": [\"metric:AveragePrecision\", \"age:overall_age\", \"gender:overall_gender\"]}"); - var histories_all = JSON.parse("{\"0\": [\"0.9881305637982196\", \"0.9846642424596361\", \"1.0\", \"0.9774150023005145\", \"1.0\"], \"1\": [\"0.16666666666666666\", \"0.12355993933932125\", \"0.0869232309681681\", \"0.16848545439520507\", \"0.2112634461547963\"], \"2\": [\"0.25\", \"0.2830041880864144\", \"0.41993045475460566\", \"0.43225179380317375\", \"0.5597221796411271\"], \"3\": [\"0.2\", \"0.14449726458815493\", \"0.22421798595769948\", \"0.14629213269349095\", \"0.05247796386824151\"], \"4\": [\"0.8048507462686567\", \"0.9342565165150828\", \"0.8326477184475645\", \"0.7837802923586923\", \"0.6153230961656271\"], \"5\": [\"0.33532536520584333\", \"0.4483547925594397\", \"0.583228952457814\", \"0.6933369218991075\", \"0.629190295280195\"], \"6\": [\"0.9434889434889435\", \"1.0\", \"1.0\", \"0.8488761897437797\", \"0.6994719852432872\"], \"7\": [\"0.1276595744680851\", \"0.12665371341896167\", \"0.10203420425805942\", \"0.18930572267029583\", \"0.19195177972424882\"], \"8\": [\"0.5454545454545454\", \"0.4875310216838917\", \"0.3320599333256127\", \"0.22307578639712178\", \"0.15317291426986096\"], \"9\": [\"0.20689655172413793\", \"0.20145989190511068\", \"0.2731344575033684\", \"0.1656436918849981\", \"0.19540560065803958\"], \"10\": [\"0.8674855654930375\", \"0.8972268034820535\", \"0.8892416445616308\", \"0.9586238683364244\", \"1.0\"], \"11\": [\"0.24891113213186\", \"0.1575636032394537\", \"0.3054230944545963\", \"0.3397461998845977\", \"0.338375308267361\"], \"12\": [\"0.9312130177514792\", \"0.9841155604894851\", \"1.0\", \"0.962039493055335\", \"0.8425878782852144\"], \"13\": [\"0.15294117647058825\", \"0.20859391120752838\", \"0.14341995448654027\", \"0.0898049900674727\", \"0.35021070503266927\"], \"14\": [\"0.38235294117647056\", \"0.4096407769458771\", \"0.46890653428540685\", \"0.5100196064614011\", \"0.6633640244378706\"], \"15\": [\"0.2184873949579832\", \"0.1329796793667143\", \"0.16945647320999394\", \"0.29799798314722303\", \"0.2689648561382229\"], \"16\": [\"0.830335624386325\", \"0.9704158695441639\", \"0.9416619108258805\", \"0.8603671945292782\", \"0.8819785988838736\"], \"17\": [\"0.21237283774963328\", \"0.1818051388150806\", \"0.29074966402637775\", \"0.2710695923097229\", \"0.2546698742212553\"], \"18\": [\"0.9506995336442372\", \"1.0\", \"1.0\", \"0.9357066407302105\", \"0.9992375832300644\"], \"19\": [\"0.08695652173913043\", \"0.0283564318005148\", \"0.0\", \"0.0\", \"0.0\"], \"20\": [\"0.35294117647058826\", \"0.494637462315184\", \"0.47381247301334384\", \"0.4740394992563078\", \"0.5417864174811365\"], \"21\": [\"0.13953488372093023\", \"0.030782550341716897\", \"0.06214736416791168\", \"0.13897662573700637\", \"0.14984415071322915\"], \"22\": [\"0.8393848105279849\", \"0.916293454457296\", \"0.8701754081154712\", \"0.7428676909929434\", \"0.6672561518819491\"], \"23\": [\"0.17930950065270065\", \"0.1118838751608168\", \"0.0\", \"0.10268131049750805\", \"0.14136895175804054\"], \"24\": [\"0.9414651244304241\", \"0.6587923737710815\", \"0.7220200063306562\", \"0.629975663705904\", \"0.7973801920973087\"], \"25\": [\"0.12337662337662338\", \"0.31019591821104153\", \"0.36339074711680414\", \"0.37494996097136374\", \"0.32636977298833375\"], \"26\": [\"0.37254901960784315\", \"0.4531488417238344\", \"0.6367861597663401\", \"0.7816695066949879\", \"0.6777660057428346\"], \"27\": [\"0.18536585365853658\", \"0.19641463540287019\", \"0.05131505489328392\", \"0.21948175592804067\", \"0.18392049817703468\"], \"28\": [\"0.8409644371667295\", \"0.8406569558561543\", \"0.7743035610024097\", \"0.8086166367387012\", \"0.8049443967953129\"], \"29\": [\"0.18752991294664764\", \"0.26738811163079496\", \"0.1982048978346155\", \"0.20103578588117713\", \"0.07940893288934088\"]}"); + var histories_all = JSON.parse("{\"0\": [\"0.9910979228486647\", \"0.9551027885687664\", \"0.9476821492397716\", \"1.0\", \"0.9029265334051461\"], \"1\": [\"0.25\", \"0.24149580817347682\", \"0.17262193517018803\", \"0.22535926073266713\", \"0.08122629647048757\"], \"2\": [\"0.25\", \"0.16161902517697557\", \"0.19317238038191537\", \"0.33106000906367167\", \"0.3428178942030108\"], \"3\": [\"0.25\", \"0.3025023221105475\", \"0.40093233033145315\", \"0.40628480390712407\", \"0.2139652239476544\"], \"4\": [\"0.8391791044776119\", \"0.7379332434324294\", \"0.6852477577575716\", \"0.754138638603504\", \"0.8703993559208607\"], \"5\": [\"0.13118961352657005\", \"0.2234672098124077\", \"0.13923300434824976\", \"0.34922819769798014\", \"0.1871597497769886\"], \"6\": [\"0.9680589680589681\", \"0.9119007184395003\", \"1.0\", \"1.0\", \"1.0\"], \"7\": [\"0.1875\", \"0.2538006437107212\", \"0.4403010484145677\", \"0.32031616408149616\", \"0.37559069492862046\"], \"8\": [\"0.4090909090909091\", \"0.43837451064398497\", \"0.5600234632560943\", \"0.5412184147272299\", \"0.4473040461357677\"], \"9\": [\"0.2571428571428571\", \"0.08387545237734079\", \"0.1627556381278868\", \"0.20030989158179216\", \"0.15299651681419382\"], \"10\": [\"0.852484999433941\", \"0.8792906522229355\", \"0.8284606379279933\", \"0.9129662152294957\", \"0.9620254405731373\"], \"11\": [\"0.32173933819025763\", \"0.3194197492378962\", \"0.36016780242689395\", \"0.38168552986513293\", \"0.12722149357683438\"], \"12\": [\"0.9563609467455622\", \"0.9953473878934656\", \"1.0\", \"1.0\", \"1.0\"], \"13\": [\"0.2222222222222222\", \"0.11860156583727859\", \"0.3917822836130673\", \"0.4233227129081373\", \"0.5288538925268242\"], \"14\": [\"0.29411764705882354\", \"0.27533582846259363\", \"0.2843500366692596\", \"0.26602849961640634\", \"0.16763191666623203\"], \"15\": [\"0.25316455696202533\", \"0.323838818797371\", \"0.303620226197352\", \"0.41046833006391265\", \"0.3845286095927599\"], \"16\": [\"0.81299651878961\", \"0.802123500698371\", \"0.9162659623437334\", \"0.9217841954948318\", \"0.9017499847161142\"], \"17\": [\"0.24706249745222636\", \"0.1401421840863098\", \"0.043331174237276615\", \"0.13896997025369956\", \"0.0\"], \"18\": [\"0.9726848767488341\", \"0.9627164745384116\", \"0.9822242727928177\", \"0.9264119939813182\", \"1.0\"], \"19\": [\"0.125\", \"0.0\", \"0.0\", \"0.09179153637213769\", \"0.03622574533982135\"], \"20\": [\"0.23529411764705882\", \"0.3247727165160673\", \"0.44073235504667096\", \"0.43667117508149916\", \"0.3225955452123267\"], \"21\": [\"0.16326530612244897\", \"0.07080023250253471\", \"0.1689355745584472\", \"0.04935180293859506\", \"0.02683047803223798\"], \"22\": [\"0.842635167274457\", \"0.94235298646717\", \"0.7742650003062747\", \"0.7723691479553396\", \"0.673949872142709\"], \"23\": [\"0.207600954098402\", \"0.27683100742807426\", \"0.20516774249402575\", \"0.217530998883252\", \"0.21703466247461362\"], \"24\": [\"0.9649491763056431\", \"0.9935535980981289\", \"0.9257441699553686\", \"0.7810581620398953\", \"0.8386891937509838\"], \"25\": [\"0.18181818181818182\", \"0.12781467306126143\", \"0.1488402472474146\", \"0.16734649474642535\", \"0.0\"], \"26\": [\"0.27450980392156865\", \"0.25434997869293496\", \"0.3290002533939981\", \"0.3854039025234891\", \"0.42586954322842646\"], \"27\": [\"0.21875\", \"0.24353068059100832\", \"0.25985287146449176\", \"0.09560137627672127\", \"0.10824119394903231\"], \"28\": [\"0.8308141243649494\", \"0.9715901949951978\", \"1.0\", \"0.9446511604371872\", \"0.9174962836932693\"], \"29\": [\"0.23163107098947502\", \"0.10732818400826394\", \"0.08121729905649898\", \"0.10179918944272683\", \"0.010462741127687983\"]}"); var thresholds_all = JSON.parse("{\"0\": \"0.7\", \"1\": \"0.7\", \"2\": \"0.7\", \"3\": \"0.7\", \"4\": \"0.7\", \"5\": \"0.7\", \"6\": \"0.7\", \"7\": \"0.7\", \"8\": \"0.7\", \"9\": \"0.7\", \"10\": \"0.7\", \"11\": \"0.7\", \"12\": \"0.7\", \"13\": \"0.7\", \"14\": \"0.7\", \"15\": \"0.7\", \"16\": \"0.7\", \"17\": \"0.7\", \"18\": \"0.7\", \"19\": \"0.7\", \"20\": \"0.7\", \"21\": \"0.7\", \"22\": \"0.7\", \"23\": \"0.7\", \"24\": \"0.7\", \"25\": \"0.7\", \"26\": \"0.7\", \"27\": \"0.7\", \"28\": \"0.7\", \"29\": \"0.7\"}"); - var trends_all = JSON.parse("{\"0\": \"neutral\", \"1\": \"positive\", \"2\": \"positive\", \"3\": \"negative\", \"4\": \"negative\", \"5\": \"positive\", \"6\": \"negative\", \"7\": \"positive\", \"8\": \"negative\", \"9\": \"neutral\", \"10\": \"positive\", \"11\": \"positive\", \"12\": \"negative\", \"13\": \"positive\", \"14\": \"positive\", \"15\": \"positive\", \"16\": \"neutral\", \"17\": \"positive\", \"18\": \"neutral\", \"19\": \"negative\", \"20\": \"positive\", \"21\": \"positive\", \"22\": \"negative\", \"23\": \"neutral\", \"24\": \"negative\", \"25\": \"positive\", \"26\": \"positive\", \"27\": \"neutral\", \"28\": \"negative\", \"29\": \"negative\"}"); - var passed_all = JSON.parse("{\"0\": true, \"1\": false, \"2\": false, \"3\": false, \"4\": false, \"5\": false, \"6\": false, \"7\": false, \"8\": false, \"9\": false, \"10\": true, \"11\": false, \"12\": true, \"13\": false, \"14\": false, \"15\": false, \"16\": true, \"17\": false, \"18\": true, \"19\": false, \"20\": false, \"21\": false, \"22\": false, \"23\": false, \"24\": true, \"25\": false, \"26\": false, \"27\": false, \"28\": true, \"29\": false}"); + var trends_all = JSON.parse("{\"0\": \"negative\", \"1\": \"negative\", \"2\": \"positive\", \"3\": \"neutral\", \"4\": \"neutral\", \"5\": \"positive\", \"6\": \"positive\", \"7\": \"positive\", \"8\": \"positive\", \"9\": \"neutral\", \"10\": \"positive\", \"11\": \"negative\", \"12\": \"neutral\", \"13\": \"positive\", \"14\": \"negative\", \"15\": \"positive\", \"16\": \"positive\", \"17\": \"negative\", \"18\": \"neutral\", \"19\": \"neutral\", \"20\": \"positive\", \"21\": \"negative\", \"22\": \"negative\", \"23\": \"neutral\", \"24\": \"negative\", \"25\": \"negative\", \"26\": \"positive\", \"27\": \"negative\", \"28\": \"positive\", \"29\": \"negative\"}"); + var passed_all = JSON.parse("{\"0\": true, \"1\": false, \"2\": false, \"3\": false, \"4\": true, \"5\": false, \"6\": true, \"7\": false, \"8\": false, \"9\": false, \"10\": true, \"11\": false, \"12\": true, \"13\": false, \"14\": false, \"15\": false, \"16\": true, \"17\": false, \"18\": true, \"19\": false, \"20\": false, \"21\": false, \"22\": false, \"23\": false, \"24\": true, \"25\": false, \"26\": false, \"27\": false, \"28\": true, \"29\": false}"); var names_all = JSON.parse("{\"0\": \"Accuracy\", \"1\": \"Precision\", \"2\": \"Recall\", \"3\": \"F1 Score\", \"4\": \"AUROC\", \"5\": \"AveragePrecision\", \"6\": \"Accuracy\", \"7\": \"Precision\", \"8\": \"Recall\", \"9\": \"F1 Score\", \"10\": \"AUROC\", \"11\": \"AveragePrecision\", \"12\": \"Accuracy\", \"13\": \"Precision\", \"14\": \"Recall\", \"15\": \"F1 Score\", \"16\": \"AUROC\", \"17\": \"AveragePrecision\", \"18\": \"Accuracy\", \"19\": \"Precision\", \"20\": \"Recall\", \"21\": \"F1 Score\", \"22\": \"AUROC\", \"23\": \"AveragePrecision\", \"24\": \"Accuracy\", \"25\": \"Precision\", \"26\": \"Recall\", \"27\": \"F1 Score\", \"28\": \"AUROC\", \"29\": \"AveragePrecision\"}"); var timestamps_all = JSON.parse("{\"0\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"1\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"2\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"3\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"4\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"5\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"6\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"7\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"8\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"9\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"10\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"11\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"12\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"13\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"14\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"15\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"16\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"17\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"18\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"19\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"20\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"21\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"22\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"23\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"24\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"25\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"26\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"27\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"28\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"29\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"]}"); @@ -2818,10 +2818,10 @@

Ethical Considerations

} } var slices_all = JSON.parse("{\"0\": [\"metric:Accuracy\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"1\": [\"metric:Precision\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"2\": [\"metric:Recall\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"3\": [\"metric:F1 Score\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"4\": [\"metric:AUROC\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"5\": [\"metric:AveragePrecision\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"6\": [\"metric:Accuracy\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"7\": [\"metric:Precision\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"8\": [\"metric:Recall\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"9\": [\"metric:F1 Score\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"10\": [\"metric:AUROC\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"11\": [\"metric:AveragePrecision\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"12\": [\"metric:Accuracy\", \"gender:M\", \"age:overall_age\"], \"13\": [\"metric:Precision\", \"gender:M\", \"age:overall_age\"], \"14\": [\"metric:Recall\", \"gender:M\", \"age:overall_age\"], \"15\": [\"metric:F1 Score\", \"gender:M\", \"age:overall_age\"], \"16\": [\"metric:AUROC\", \"gender:M\", \"age:overall_age\"], \"17\": [\"metric:AveragePrecision\", \"gender:M\", \"age:overall_age\"], \"18\": [\"metric:Accuracy\", \"gender:F\", \"age:overall_age\"], \"19\": [\"metric:Precision\", \"gender:F\", \"age:overall_age\"], \"20\": [\"metric:Recall\", \"gender:F\", \"age:overall_age\"], \"21\": [\"metric:F1 Score\", \"gender:F\", \"age:overall_age\"], \"22\": [\"metric:AUROC\", \"gender:F\", \"age:overall_age\"], \"23\": [\"metric:AveragePrecision\", \"gender:F\", \"age:overall_age\"], \"24\": [\"metric:Accuracy\", \"age:overall_age\", \"gender:overall_gender\"], \"25\": [\"metric:Precision\", \"age:overall_age\", \"gender:overall_gender\"], \"26\": [\"metric:Recall\", \"age:overall_age\", \"gender:overall_gender\"], \"27\": [\"metric:F1 Score\", \"age:overall_age\", \"gender:overall_gender\"], \"28\": [\"metric:AUROC\", \"age:overall_age\", \"gender:overall_gender\"], \"29\": [\"metric:AveragePrecision\", \"age:overall_age\", \"gender:overall_gender\"]}"); - var histories_all = JSON.parse("{\"0\": [\"0.9881305637982196\", \"0.9846642424596361\", \"1.0\", \"0.9774150023005145\", \"1.0\"], \"1\": [\"0.16666666666666666\", \"0.12355993933932125\", \"0.0869232309681681\", \"0.16848545439520507\", \"0.2112634461547963\"], \"2\": [\"0.25\", \"0.2830041880864144\", \"0.41993045475460566\", \"0.43225179380317375\", \"0.5597221796411271\"], \"3\": [\"0.2\", \"0.14449726458815493\", \"0.22421798595769948\", \"0.14629213269349095\", \"0.05247796386824151\"], \"4\": [\"0.8048507462686567\", \"0.9342565165150828\", \"0.8326477184475645\", \"0.7837802923586923\", \"0.6153230961656271\"], \"5\": [\"0.33532536520584333\", \"0.4483547925594397\", \"0.583228952457814\", \"0.6933369218991075\", \"0.629190295280195\"], \"6\": [\"0.9434889434889435\", \"1.0\", \"1.0\", \"0.8488761897437797\", \"0.6994719852432872\"], \"7\": [\"0.1276595744680851\", \"0.12665371341896167\", \"0.10203420425805942\", \"0.18930572267029583\", \"0.19195177972424882\"], \"8\": [\"0.5454545454545454\", \"0.4875310216838917\", \"0.3320599333256127\", \"0.22307578639712178\", \"0.15317291426986096\"], \"9\": [\"0.20689655172413793\", \"0.20145989190511068\", \"0.2731344575033684\", \"0.1656436918849981\", \"0.19540560065803958\"], \"10\": [\"0.8674855654930375\", \"0.8972268034820535\", \"0.8892416445616308\", \"0.9586238683364244\", \"1.0\"], \"11\": [\"0.24891113213186\", \"0.1575636032394537\", \"0.3054230944545963\", \"0.3397461998845977\", \"0.338375308267361\"], \"12\": [\"0.9312130177514792\", \"0.9841155604894851\", \"1.0\", \"0.962039493055335\", \"0.8425878782852144\"], \"13\": [\"0.15294117647058825\", \"0.20859391120752838\", \"0.14341995448654027\", \"0.0898049900674727\", \"0.35021070503266927\"], \"14\": [\"0.38235294117647056\", \"0.4096407769458771\", \"0.46890653428540685\", \"0.5100196064614011\", \"0.6633640244378706\"], \"15\": [\"0.2184873949579832\", \"0.1329796793667143\", \"0.16945647320999394\", \"0.29799798314722303\", \"0.2689648561382229\"], \"16\": [\"0.830335624386325\", \"0.9704158695441639\", \"0.9416619108258805\", \"0.8603671945292782\", \"0.8819785988838736\"], \"17\": [\"0.21237283774963328\", \"0.1818051388150806\", \"0.29074966402637775\", \"0.2710695923097229\", \"0.2546698742212553\"], \"18\": [\"0.9506995336442372\", \"1.0\", \"1.0\", \"0.9357066407302105\", \"0.9992375832300644\"], \"19\": [\"0.08695652173913043\", \"0.0283564318005148\", \"0.0\", \"0.0\", \"0.0\"], \"20\": [\"0.35294117647058826\", \"0.494637462315184\", \"0.47381247301334384\", \"0.4740394992563078\", \"0.5417864174811365\"], \"21\": [\"0.13953488372093023\", \"0.030782550341716897\", \"0.06214736416791168\", \"0.13897662573700637\", \"0.14984415071322915\"], \"22\": [\"0.8393848105279849\", \"0.916293454457296\", \"0.8701754081154712\", \"0.7428676909929434\", \"0.6672561518819491\"], \"23\": [\"0.17930950065270065\", \"0.1118838751608168\", \"0.0\", \"0.10268131049750805\", \"0.14136895175804054\"], \"24\": [\"0.9414651244304241\", \"0.6587923737710815\", \"0.7220200063306562\", \"0.629975663705904\", \"0.7973801920973087\"], \"25\": [\"0.12337662337662338\", \"0.31019591821104153\", \"0.36339074711680414\", \"0.37494996097136374\", \"0.32636977298833375\"], \"26\": [\"0.37254901960784315\", \"0.4531488417238344\", \"0.6367861597663401\", \"0.7816695066949879\", \"0.6777660057428346\"], \"27\": [\"0.18536585365853658\", \"0.19641463540287019\", \"0.05131505489328392\", \"0.21948175592804067\", \"0.18392049817703468\"], \"28\": [\"0.8409644371667295\", \"0.8406569558561543\", \"0.7743035610024097\", \"0.8086166367387012\", \"0.8049443967953129\"], \"29\": [\"0.18752991294664764\", \"0.26738811163079496\", \"0.1982048978346155\", \"0.20103578588117713\", \"0.07940893288934088\"]}"); + var histories_all = JSON.parse("{\"0\": [\"0.9910979228486647\", \"0.9551027885687664\", \"0.9476821492397716\", \"1.0\", \"0.9029265334051461\"], \"1\": [\"0.25\", \"0.24149580817347682\", \"0.17262193517018803\", \"0.22535926073266713\", \"0.08122629647048757\"], \"2\": [\"0.25\", \"0.16161902517697557\", \"0.19317238038191537\", \"0.33106000906367167\", \"0.3428178942030108\"], \"3\": [\"0.25\", \"0.3025023221105475\", \"0.40093233033145315\", \"0.40628480390712407\", \"0.2139652239476544\"], \"4\": [\"0.8391791044776119\", \"0.7379332434324294\", \"0.6852477577575716\", \"0.754138638603504\", \"0.8703993559208607\"], \"5\": [\"0.13118961352657005\", \"0.2234672098124077\", \"0.13923300434824976\", \"0.34922819769798014\", \"0.1871597497769886\"], \"6\": [\"0.9680589680589681\", \"0.9119007184395003\", \"1.0\", \"1.0\", \"1.0\"], \"7\": [\"0.1875\", \"0.2538006437107212\", \"0.4403010484145677\", \"0.32031616408149616\", \"0.37559069492862046\"], \"8\": [\"0.4090909090909091\", \"0.43837451064398497\", \"0.5600234632560943\", \"0.5412184147272299\", \"0.4473040461357677\"], \"9\": [\"0.2571428571428571\", \"0.08387545237734079\", \"0.1627556381278868\", \"0.20030989158179216\", \"0.15299651681419382\"], \"10\": [\"0.852484999433941\", \"0.8792906522229355\", \"0.8284606379279933\", \"0.9129662152294957\", \"0.9620254405731373\"], \"11\": [\"0.32173933819025763\", \"0.3194197492378962\", \"0.36016780242689395\", \"0.38168552986513293\", \"0.12722149357683438\"], \"12\": [\"0.9563609467455622\", \"0.9953473878934656\", \"1.0\", \"1.0\", \"1.0\"], \"13\": [\"0.2222222222222222\", \"0.11860156583727859\", \"0.3917822836130673\", \"0.4233227129081373\", \"0.5288538925268242\"], \"14\": [\"0.29411764705882354\", \"0.27533582846259363\", \"0.2843500366692596\", \"0.26602849961640634\", \"0.16763191666623203\"], \"15\": [\"0.25316455696202533\", \"0.323838818797371\", \"0.303620226197352\", \"0.41046833006391265\", \"0.3845286095927599\"], \"16\": [\"0.81299651878961\", \"0.802123500698371\", \"0.9162659623437334\", \"0.9217841954948318\", \"0.9017499847161142\"], \"17\": [\"0.24706249745222636\", \"0.1401421840863098\", \"0.043331174237276615\", \"0.13896997025369956\", \"0.0\"], \"18\": [\"0.9726848767488341\", \"0.9627164745384116\", \"0.9822242727928177\", \"0.9264119939813182\", \"1.0\"], \"19\": [\"0.125\", \"0.0\", \"0.0\", \"0.09179153637213769\", \"0.03622574533982135\"], \"20\": [\"0.23529411764705882\", \"0.3247727165160673\", \"0.44073235504667096\", \"0.43667117508149916\", \"0.3225955452123267\"], \"21\": [\"0.16326530612244897\", \"0.07080023250253471\", \"0.1689355745584472\", \"0.04935180293859506\", \"0.02683047803223798\"], \"22\": [\"0.842635167274457\", \"0.94235298646717\", \"0.7742650003062747\", \"0.7723691479553396\", \"0.673949872142709\"], \"23\": [\"0.207600954098402\", \"0.27683100742807426\", \"0.20516774249402575\", \"0.217530998883252\", \"0.21703466247461362\"], \"24\": [\"0.9649491763056431\", \"0.9935535980981289\", \"0.9257441699553686\", \"0.7810581620398953\", \"0.8386891937509838\"], \"25\": [\"0.18181818181818182\", \"0.12781467306126143\", \"0.1488402472474146\", \"0.16734649474642535\", \"0.0\"], \"26\": [\"0.27450980392156865\", \"0.25434997869293496\", \"0.3290002533939981\", \"0.3854039025234891\", \"0.42586954322842646\"], \"27\": [\"0.21875\", \"0.24353068059100832\", \"0.25985287146449176\", \"0.09560137627672127\", \"0.10824119394903231\"], \"28\": [\"0.8308141243649494\", \"0.9715901949951978\", \"1.0\", \"0.9446511604371872\", \"0.9174962836932693\"], \"29\": [\"0.23163107098947502\", \"0.10732818400826394\", \"0.08121729905649898\", \"0.10179918944272683\", \"0.010462741127687983\"]}"); var thresholds_all = JSON.parse("{\"0\": \"0.7\", \"1\": \"0.7\", \"2\": \"0.7\", \"3\": \"0.7\", \"4\": \"0.7\", \"5\": \"0.7\", \"6\": \"0.7\", \"7\": \"0.7\", \"8\": \"0.7\", \"9\": \"0.7\", \"10\": \"0.7\", \"11\": \"0.7\", \"12\": \"0.7\", \"13\": \"0.7\", \"14\": \"0.7\", \"15\": \"0.7\", \"16\": \"0.7\", \"17\": \"0.7\", \"18\": \"0.7\", \"19\": \"0.7\", \"20\": \"0.7\", \"21\": \"0.7\", \"22\": \"0.7\", \"23\": \"0.7\", \"24\": \"0.7\", \"25\": \"0.7\", \"26\": \"0.7\", \"27\": \"0.7\", \"28\": \"0.7\", \"29\": \"0.7\"}"); - var trends_all = JSON.parse("{\"0\": \"neutral\", \"1\": \"positive\", \"2\": \"positive\", \"3\": \"negative\", \"4\": \"negative\", \"5\": \"positive\", \"6\": \"negative\", \"7\": \"positive\", \"8\": \"negative\", \"9\": \"neutral\", \"10\": \"positive\", \"11\": \"positive\", \"12\": \"negative\", \"13\": \"positive\", \"14\": \"positive\", \"15\": \"positive\", \"16\": \"neutral\", \"17\": \"positive\", \"18\": \"neutral\", \"19\": \"negative\", \"20\": \"positive\", \"21\": \"positive\", \"22\": \"negative\", \"23\": \"neutral\", \"24\": \"negative\", \"25\": \"positive\", \"26\": \"positive\", \"27\": \"neutral\", \"28\": \"negative\", \"29\": \"negative\"}"); - var passed_all = JSON.parse("{\"0\": true, \"1\": false, \"2\": false, \"3\": false, \"4\": false, \"5\": false, \"6\": false, \"7\": false, \"8\": false, \"9\": false, \"10\": true, \"11\": false, \"12\": true, \"13\": false, \"14\": false, \"15\": false, \"16\": true, \"17\": false, \"18\": true, \"19\": false, \"20\": false, \"21\": false, \"22\": false, \"23\": false, \"24\": true, \"25\": false, \"26\": false, \"27\": false, \"28\": true, \"29\": false}"); + var trends_all = JSON.parse("{\"0\": \"negative\", \"1\": \"negative\", \"2\": \"positive\", \"3\": \"neutral\", \"4\": \"neutral\", \"5\": \"positive\", \"6\": \"positive\", \"7\": \"positive\", \"8\": \"positive\", \"9\": \"neutral\", \"10\": \"positive\", \"11\": \"negative\", \"12\": \"neutral\", \"13\": \"positive\", \"14\": \"negative\", \"15\": \"positive\", \"16\": \"positive\", \"17\": \"negative\", \"18\": \"neutral\", \"19\": \"neutral\", \"20\": \"positive\", \"21\": \"negative\", \"22\": \"negative\", \"23\": \"neutral\", \"24\": \"negative\", \"25\": \"negative\", \"26\": \"positive\", \"27\": \"negative\", \"28\": \"positive\", \"29\": \"negative\"}"); + var passed_all = JSON.parse("{\"0\": true, \"1\": false, \"2\": false, \"3\": false, \"4\": true, \"5\": false, \"6\": true, \"7\": false, \"8\": false, \"9\": false, \"10\": true, \"11\": false, \"12\": true, \"13\": false, \"14\": false, \"15\": false, \"16\": true, \"17\": false, \"18\": true, \"19\": false, \"20\": false, \"21\": false, \"22\": false, \"23\": false, \"24\": true, \"25\": false, \"26\": false, \"27\": false, \"28\": true, \"29\": false}"); var names_all = JSON.parse("{\"0\": \"Accuracy\", \"1\": \"Precision\", \"2\": \"Recall\", \"3\": \"F1 Score\", \"4\": \"AUROC\", \"5\": \"AveragePrecision\", \"6\": \"Accuracy\", \"7\": \"Precision\", \"8\": \"Recall\", \"9\": \"F1 Score\", \"10\": \"AUROC\", \"11\": \"AveragePrecision\", \"12\": \"Accuracy\", \"13\": \"Precision\", \"14\": \"Recall\", \"15\": \"F1 Score\", \"16\": \"AUROC\", \"17\": \"AveragePrecision\", \"18\": \"Accuracy\", \"19\": \"Precision\", \"20\": \"Recall\", \"21\": \"F1 Score\", \"22\": \"AUROC\", \"23\": \"AveragePrecision\", \"24\": \"Accuracy\", \"25\": \"Precision\", \"26\": \"Recall\", \"27\": \"F1 Score\", \"28\": \"AUROC\", \"29\": \"AveragePrecision\"}"); var timestamps_all = JSON.parse("{\"0\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"1\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"2\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"3\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"4\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"5\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"6\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"7\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"8\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"9\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"10\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"11\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"12\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"13\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"14\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"15\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"16\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"17\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"18\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"19\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"20\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"21\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"22\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"23\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"24\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"25\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"26\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"27\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"28\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"29\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"]}"); diff --git a/api/tutorials/nihcxr/cxr_classification.html b/api/tutorials/nihcxr/cxr_classification.html index 7f2c4cff6..0b8fce16a 100644 --- a/api/tutorials/nihcxr/cxr_classification.html +++ b/api/tutorials/nihcxr/cxr_classification.html @@ -496,74 +496,74 @@

Generate Historical Reports 
-Flattening the indices: 100%|████████| 1000/1000 [00:54<00:00, 18.51 examples/s]
-Flattening the indices: 100%|████| 1000/1000 [00:00<00:00, 543514.84 examples/s]
-Filter: 100%|████████████████████| 1000/1000 [00:00<00:00, 187866.34 examples/s]
-Map: 100%|███████████████████████████| 400/400 [00:00<00:00, 1778.49 examples/s]
-Filter -> Patient Gender:M: 100%|███| 400/400 [00:00<00:00, 42806.66 examples/s]
-Filter -> Patient Gender:F: 100%|███| 400/400 [00:00<00:00, 34901.64 examples/s]
-Filter -> overall: 100%|████████████| 400/400 [00:00<00:00, 46077.33 examples/s]
-Filter -> Patient Age:[19 - 35]: 100%|█| 400/400 [00:00<00:00, 41831.14 examples
-Filter -> Patient Age:[35 - 65]: 100%|█| 400/400 [00:00<00:00, 43028.43 examples
-Filter -> Patient Age:[65 - 100]: 100%|█| 400/400 [00:00<00:00, 41388.43 example
+Flattening the indices: 100%|████████| 1000/1000 [00:52<00:00, 18.99 examples/s]
+Flattening the indices: 100%|████| 1000/1000 [00:00<00:00, 551301.79 examples/s]
+Filter: 100%|████████████████████| 1000/1000 [00:00<00:00, 229988.70 examples/s]
+Map: 100%|███████████████████████████| 400/400 [00:00<00:00, 1559.55 examples/s]
+Filter -> Patient Gender:M: 100%|███| 400/400 [00:00<00:00, 42669.49 examples/s]
+Filter -> Patient Gender:F: 100%|███| 400/400 [00:00<00:00, 33734.57 examples/s]
+Filter -> overall: 100%|████████████| 400/400 [00:00<00:00, 45108.53 examples/s]
+Filter -> Patient Age:[19 - 35]: 100%|█| 400/400 [00:00<00:00, 41567.89 examples
+Filter -> Patient Age:[35 - 65]: 100%|█| 400/400 [00:00<00:00, 41475.40 examples
+Filter -> Patient Age:[65 - 100]: 100%|█| 400/400 [00:00<00:00, 39719.73 example
 Filter -> Patient Age:[19 - 35]&Patient Gender:M: 100%|█| 400/400 [00:00<00:00,
 Filter -> Patient Age:[19 - 35]&Patient Gender:F: 100%|█| 400/400 [00:00<00:00,
 Filter -> Patient Age:[35 - 65]&Patient Gender:M: 100%|█| 400/400 [00:00<00:00,
 Filter -> Patient Age:[35 - 65]&Patient Gender:F: 100%|█| 400/400 [00:00<00:00,
 Filter -> Patient Age:[65 - 100]&Patient Gender:M: 100%|█| 400/400 [00:00<00:00,
 Filter -> Patient Age:[65 - 100]&Patient Gender:F: 100%|█| 400/400 [00:00<00:00,
-Filter -> overall: 100%|████████████| 400/400 [00:00<00:00, 48508.69 examples/s]
-Flattening the indices: 100%|████████| 1000/1000 [00:51<00:00, 19.38 examples/s]
-Flattening the indices: 100%|████| 1000/1000 [00:00<00:00, 554508.73 examples/s]
-Filter: 100%|████████████████████| 1000/1000 [00:00<00:00, 239976.20 examples/s]
-Map: 100%|███████████████████████████| 396/396 [00:00<00:00, 1816.81 examples/s]
-Filter -> Patient Gender:M: 100%|███| 396/396 [00:00<00:00, 42819.98 examples/s]
-Filter -> Patient Gender:F: 100%|███| 396/396 [00:00<00:00, 43439.28 examples/s]
-Filter -> overall: 100%|████████████| 396/396 [00:00<00:00, 44934.11 examples/s]
-Filter -> Patient Age:[19 - 35]: 100%|█| 396/396 [00:00<00:00, 39218.54 examples
-Filter -> Patient Age:[35 - 65]: 100%|█| 396/396 [00:00<00:00, 41051.52 examples
-Filter -> Patient Age:[65 - 100]: 100%|█| 396/396 [00:00<00:00, 40678.51 example
+Filter -> overall: 100%|████████████| 400/400 [00:00<00:00, 45740.66 examples/s]
+Flattening the indices: 100%|████████| 1000/1000 [00:53<00:00, 18.55 examples/s]
+Flattening the indices: 100%|████| 1000/1000 [00:00<00:00, 559315.11 examples/s]
+Filter: 100%|████████████████████| 1000/1000 [00:00<00:00, 234646.38 examples/s]
+Map: 100%|███████████████████████████| 396/396 [00:00<00:00, 1796.22 examples/s]
+Filter -> Patient Gender:M: 100%|███| 396/396 [00:00<00:00, 42756.05 examples/s]
+Filter -> Patient Gender:F: 100%|███| 396/396 [00:00<00:00, 41877.47 examples/s]
+Filter -> overall: 100%|████████████| 396/396 [00:00<00:00, 44262.34 examples/s]
+Filter -> Patient Age:[19 - 35]: 100%|█| 396/396 [00:00<00:00, 39876.70 examples
+Filter -> Patient Age:[35 - 65]: 100%|█| 396/396 [00:00<00:00, 41115.54 examples
+Filter -> Patient Age:[65 - 100]: 100%|█| 396/396 [00:00<00:00, 40568.23 example
 Filter -> Patient Age:[19 - 35]&Patient Gender:M: 100%|█| 396/396 [00:00<00:00,
 Filter -> Patient Age:[19 - 35]&Patient Gender:F: 100%|█| 396/396 [00:00<00:00,
 Filter -> Patient Age:[35 - 65]&Patient Gender:M: 100%|█| 396/396 [00:00<00:00,
 Filter -> Patient Age:[35 - 65]&Patient Gender:F: 100%|█| 396/396 [00:00<00:00,
 Filter -> Patient Age:[65 - 100]&Patient Gender:M: 100%|█| 396/396 [00:00<00:00,
 Filter -> Patient Age:[65 - 100]&Patient Gender:F: 100%|█| 396/396 [00:00<00:00,
-Filter -> overall: 100%|████████████| 396/396 [00:00<00:00, 25361.03 examples/s]
-Flattening the indices: 100%|████████| 1000/1000 [00:51<00:00, 19.26 examples/s]
-Flattening the indices: 100%|████| 1000/1000 [00:00<00:00, 551591.79 examples/s]
-Filter: 100%|████████████████████| 1000/1000 [00:00<00:00, 241024.25 examples/s]
-Map: 100%|███████████████████████████| 383/383 [00:00<00:00, 1797.95 examples/s]
-Filter -> Patient Gender:M: 100%|███| 383/383 [00:00<00:00, 42636.58 examples/s]
-Filter -> Patient Gender:F: 100%|███| 383/383 [00:00<00:00, 42604.92 examples/s]
-Filter -> overall: 100%|████████████| 383/383 [00:00<00:00, 44897.11 examples/s]
-Filter -> Patient Age:[19 - 35]: 100%|█| 383/383 [00:00<00:00, 24012.95 examples
-Filter -> Patient Age:[35 - 65]: 100%|█| 383/383 [00:00<00:00, 23006.35 examples
-Filter -> Patient Age:[65 - 100]: 100%|█| 383/383 [00:00<00:00, 24197.42 example
+Filter -> overall: 100%|████████████| 396/396 [00:00<00:00, 45328.98 examples/s]
+Flattening the indices: 100%|████████| 1000/1000 [00:50<00:00, 19.62 examples/s]
+Flattening the indices: 100%|████| 1000/1000 [00:00<00:00, 556199.97 examples/s]
+Filter: 100%|████████████████████| 1000/1000 [00:00<00:00, 237301.50 examples/s]
+Map: 100%|███████████████████████████| 383/383 [00:00<00:00, 1778.88 examples/s]
+Filter -> Patient Gender:M: 100%|███| 383/383 [00:00<00:00, 42006.65 examples/s]
+Filter -> Patient Gender:F: 100%|███| 383/383 [00:00<00:00, 42493.35 examples/s]
+Filter -> overall: 100%|████████████| 383/383 [00:00<00:00, 44476.95 examples/s]
+Filter -> Patient Age:[19 - 35]: 100%|█| 383/383 [00:00<00:00, 40546.67 examples
+Filter -> Patient Age:[35 - 65]: 100%|█| 383/383 [00:00<00:00, 40422.19 examples
+Filter -> Patient Age:[65 - 100]: 100%|█| 383/383 [00:00<00:00, 40312.64 example
 Filter -> Patient Age:[19 - 35]&Patient Gender:M: 100%|█| 383/383 [00:00<00:00,
 Filter -> Patient Age:[19 - 35]&Patient Gender:F: 100%|█| 383/383 [00:00<00:00,
 Filter -> Patient Age:[35 - 65]&Patient Gender:M: 100%|█| 383/383 [00:00<00:00,
 Filter -> Patient Age:[35 - 65]&Patient Gender:F: 100%|█| 383/383 [00:00<00:00,
 Filter -> Patient Age:[65 - 100]&Patient Gender:M: 100%|█| 383/383 [00:00<00:00,
 Filter -> Patient Age:[65 - 100]&Patient Gender:F: 100%|█| 383/383 [00:00<00:00,
-Filter -> overall: 100%|████████████| 383/383 [00:00<00:00, 45368.80 examples/s]
-Flattening the indices: 100%|████████| 1000/1000 [00:51<00:00, 19.50 examples/s]
-Flattening the indices: 100%|████| 1000/1000 [00:00<00:00, 557530.77 examples/s]
-Filter: 100%|████████████████████| 1000/1000 [00:00<00:00, 240182.33 examples/s]
-Map: 100%|███████████████████████████| 411/411 [00:00<00:00, 1811.68 examples/s]
-Filter -> Patient Gender:M: 100%|███| 411/411 [00:00<00:00, 44563.73 examples/s]
-Filter -> Patient Gender:F: 100%|███| 411/411 [00:00<00:00, 43622.12 examples/s]
-Filter -> overall: 100%|████████████| 411/411 [00:00<00:00, 45894.92 examples/s]
-Filter -> Patient Age:[19 - 35]: 100%|█| 411/411 [00:00<00:00, 42074.07 examples
-Filter -> Patient Age:[35 - 65]: 100%|█| 411/411 [00:00<00:00, 42672.94 examples
-Filter -> Patient Age:[65 - 100]: 100%|█| 411/411 [00:00<00:00, 42232.81 example
+Filter -> overall: 100%|████████████| 383/383 [00:00<00:00, 45529.53 examples/s]
+Flattening the indices: 100%|████████| 1000/1000 [00:51<00:00, 19.38 examples/s]
+Flattening the indices: 100%|████| 1000/1000 [00:00<00:00, 559762.98 examples/s]
+Filter: 100%|████████████████████| 1000/1000 [00:00<00:00, 230951.16 examples/s]
+Map: 100%|███████████████████████████| 411/411 [00:00<00:00, 1799.38 examples/s]
+Filter -> Patient Gender:M: 100%|███| 411/411 [00:00<00:00, 43468.13 examples/s]
+Filter -> Patient Gender:F: 100%|███| 411/411 [00:00<00:00, 42783.09 examples/s]
+Filter -> overall: 100%|████████████| 411/411 [00:00<00:00, 44642.21 examples/s]
+Filter -> Patient Age:[19 - 35]: 100%|█| 411/411 [00:00<00:00, 40946.77 examples
+Filter -> Patient Age:[35 - 65]: 100%|█| 411/411 [00:00<00:00, 41775.33 examples
+Filter -> Patient Age:[65 - 100]: 100%|█| 411/411 [00:00<00:00, 38797.69 example
 Filter -> Patient Age:[19 - 35]&Patient Gender:M: 100%|█| 411/411 [00:00<00:00,
 Filter -> Patient Age:[19 - 35]&Patient Gender:F: 100%|█| 411/411 [00:00<00:00,
 Filter -> Patient Age:[35 - 65]&Patient Gender:M: 100%|█| 411/411 [00:00<00:00,
 Filter -> Patient Age:[35 - 65]&Patient Gender:F: 100%|█| 411/411 [00:00<00:00,
 Filter -> Patient Age:[65 - 100]&Patient Gender:M: 100%|█| 411/411 [00:00<00:00,
 Filter -> Patient Age:[65 - 100]&Patient Gender:F: 100%|█| 411/411 [00:00<00:00,
-Filter -> overall: 100%|████████████| 411/411 [00:00<00:00, 47422.60 examples/s]
+Filter -> overall: 100%|████████████| 411/411 [00:00<00:00, 47438.26 examples/s]

CyclOps offers a package for documentation of the model through a model report. The ModelCardReport class is used to populate and generate the model report as an HTML file. The model report has the following sections:

@@ -660,13 +660,13 @@

Model Creation

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Multilabel AUROC by Pathology and Sex

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Multilabel AUROC by Pathology and Age
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[8]:
@@ -962,9 +962,9 @@ 
Multilabel AUROC by Pathology and Age
-

diff --git a/api/tutorials/nihcxr/cxr_classification.ipynb b/api/tutorials/nihcxr/cxr_classification.ipynb index f304a8048..6e97a80e0 100644 --- a/api/tutorials/nihcxr/cxr_classification.ipynb +++ b/api/tutorials/nihcxr/cxr_classification.ipynb @@ -24,10 +24,10 @@ "id": "fc1eb72a", "metadata": { "execution": { - "iopub.execute_input": "2023-12-19T19:25:35.493877Z", - "iopub.status.busy": "2023-12-19T19:25:35.493375Z", - "iopub.status.idle": "2023-12-19T19:25:40.484395Z", - "shell.execute_reply": "2023-12-19T19:25:40.483151Z" + "iopub.execute_input": "2023-12-19T22:28:38.082988Z", + "iopub.status.busy": "2023-12-19T22:28:38.082347Z", + "iopub.status.idle": "2023-12-19T22:28:44.285824Z", + "shell.execute_reply": "2023-12-19T22:28:44.285099Z" } }, "outputs": [], @@ -71,10 +71,10 @@ "id": "25c2a16f", "metadata": { "execution": { - "iopub.execute_input": "2023-12-19T19:25:40.489546Z", - "iopub.status.busy": "2023-12-19T19:25:40.489090Z", - "iopub.status.idle": "2023-12-19T19:30:58.799812Z", - "shell.execute_reply": "2023-12-19T19:30:58.797926Z" + "iopub.execute_input": "2023-12-19T22:28:44.291596Z", + "iopub.status.busy": "2023-12-19T22:28:44.291034Z", + "iopub.status.idle": "2023-12-19T22:33:59.281135Z", + "shell.execute_reply": "2023-12-19T22:33:59.279344Z" } }, "outputs": [ @@ -91,20 +91,20 @@ "output_type": "stream", "text": [ "\r", - "Flattening the indices: 100%|████████| 1000/1000 [00:54<00:00, 18.51 examples/s]\r", - "Flattening the indices: 100%|████████| 1000/1000 [00:54<00:00, 18.51 examples/s]\r\n", + "Flattening the indices: 100%|████████| 1000/1000 [00:52<00:00, 19.00 examples/s]\r", + "Flattening the indices: 100%|████████| 1000/1000 [00:52<00:00, 18.99 examples/s]\r\n", "\r", "Flattening the indices: 0%| | 0/1000 [00:00 Patient Gender:M: 0%| | 0/400 [00:00 Patient Gender:M: 100%|███| 400/400 [00:00<00:00, 42806.66 examples/s]\r\n" + "Filter -> Patient Gender:M: 100%|███| 400/400 [00:00<00:00, 42669.49 examples/s]\r\n" ] }, { @@ -127,7 +127,7 @@ "text": [ "\r", "Filter -> Patient Gender:F: 0%| | 0/400 [00:00 Patient Gender:F: 100%|███| 400/400 [00:00<00:00, 34901.64 examples/s]\r\n" + "Filter -> Patient Gender:F: 100%|███| 400/400 [00:00<00:00, 33734.57 examples/s]\r\n" ] }, { @@ -136,7 +136,7 @@ "text": [ "\r", "Filter -> overall: 0%| | 0/400 [00:00 overall: 100%|████████████| 400/400 [00:00<00:00, 46077.33 examples/s]\r\n" + "Filter -> overall: 100%|████████████| 400/400 [00:00<00:00, 45108.53 examples/s]\r\n" ] }, { @@ -145,10 +145,10 @@ "text": [ "\r", "Filter -> Patient Age:[19 - 35]: 0%| | 0/400 [00:00 Patient Age:[19 - 35]: 100%|█| 400/400 [00:00<00:00, 41831.14 examples\r\n", + "Filter -> Patient Age:[19 - 35]: 100%|█| 400/400 [00:00<00:00, 41567.89 examples\r\n", "\r", "Filter -> Patient Age:[35 - 65]: 0%| | 0/400 [00:00 Patient Age:[35 - 65]: 100%|█| 400/400 [00:00<00:00, 43028.43 examples\r\n" + "Filter -> Patient Age:[35 - 65]: 100%|█| 400/400 [00:00<00:00, 41475.40 examples\r\n" ] }, { @@ -157,7 +157,7 @@ "text": [ "\r", "Filter -> Patient Age:[65 - 100]: 0%| | 0/400 [00:00 Patient Age:[65 - 100]: 100%|█| 400/400 [00:00<00:00, 41388.43 example\r\n", + "Filter -> Patient Age:[65 - 100]: 100%|█| 400/400 [00:00<00:00, 39719.73 example\r\n", "\r", "Filter -> Patient Age:[19 - 35]&Patient Gender:M: 0%| | 0/400 [00:00 Patient Age:[19 - 35]&Patient Gender:M: 100%|█| 400/400 [00:00<00:00, \r\n" @@ -196,7 +196,7 @@ "Filter -> Patient Age:[65 - 100]&Patient Gender:F: 100%|█| 400/400 [00:00<00:00,\r\n", "\r", "Filter -> overall: 0%| | 0/400 [00:00 overall: 100%|████████████| 400/400 [00:00<00:00, 48508.69 examples/s]\r\n" + "Filter -> overall: 100%|████████████| 400/400 [00:00<00:00, 45740.66 examples/s]\r\n" ] }, { @@ -212,21 +212,14 @@ "output_type": "stream", "text": [ "\r", - "Flattening the indices: 100%|████████| 1000/1000 [00:51<00:00, 19.38 examples/s]" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\r", - "Flattening the indices: 100%|████████| 1000/1000 [00:51<00:00, 19.38 examples/s]\r\n", + "Flattening the indices: 100%|████████| 1000/1000 [00:53<00:00, 18.56 examples/s]\r", + "Flattening the indices: 100%|████████| 1000/1000 [00:53<00:00, 18.55 examples/s]\r\n", "\r", "Flattening the indices: 0%| | 0/1000 [00:00 Patient Gender:M: 0%| | 0/396 [00:00 Patient Gender:M: 100%|███| 396/396 [00:00<00:00, 42819.98 examples/s]\r\n", + "Filter -> Patient Gender:M: 0%| | 0/396 [00:00 Patient Gender:M: 100%|███| 396/396 [00:00<00:00, 42756.05 examples/s]\r\n", "\r", - "Filter -> Patient Gender:F: 0%| | 0/396 [00:00 Patient Gender:F: 100%|███| 396/396 [00:00<00:00, 43439.28 examples/s]\r\n" + "Filter -> Patient Gender:F: 0%| | 0/396 [00:00 Patient Gender:F: 100%|███| 396/396 [00:00<00:00, 41877.47 examples/s]\r\n", "\r", "Filter -> overall: 0%| | 0/396 [00:00 overall: 100%|████████████| 396/396 [00:00<00:00, 44934.11 examples/s]\r\n" + "Filter -> overall: 100%|████████████| 396/396 [00:00<00:00, 44262.34 examples/s]\r\n" ] }, { @@ -268,10 +261,9 @@ "text": [ "\r", "Filter -> Patient Age:[19 - 35]: 0%| | 0/396 [00:00 Patient Age:[19 - 35]: 100%|█| 396/396 [00:00<00:00, 39218.54 examples\r\n", + "Filter -> Patient Age:[19 - 35]: 100%|█| 396/396 [00:00<00:00, 39876.70 examples\r\n", "\r", - "Filter -> Patient Age:[35 - 65]: 0%| | 0/396 [00:00 Patient Age:[35 - 65]: 100%|█| 396/396 [00:00<00:00, 41051.52 examples\r\n" + "Filter -> Patient Age:[35 - 65]: 0%| | 0/396 [00:00 Patient Age:[65 - 100]: 0%| | 0/396 [00:00 Patient Age:[65 - 100]: 100%|█| 396/396 [00:00<00:00, 40678.51 example\r\n", + "Filter -> Patient Age:[35 - 65]: 100%|█| 396/396 [00:00<00:00, 41115.54 examples\r\n", "\r", - "Filter -> Patient Age:[19 - 35]&Patient Gender:M: 0%| | 0/396 [00:00 Patient Age:[19 - 35]&Patient Gender:M: 100%|█| 396/396 [00:00<00:00, \r\n" + "Filter -> Patient Age:[65 - 100]: 0%| | 0/396 [00:00 Patient Age:[65 - 100]: 100%|█| 396/396 [00:00<00:00, 40568.23 example\r\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ + "\r", + "Filter -> Patient Age:[19 - 35]&Patient Gender:M: 0%| | 0/396 [00:00 Patient Age:[19 - 35]&Patient Gender:M: 100%|█| 396/396 [00:00<00:00, \r\n", "\r", "Filter -> Patient Age:[19 - 35]&Patient Gender:F: 0%| | 0/396 [00:00 Patient Age:[19 - 35]&Patient Gender:F: 100%|█| 396/396 [00:00<00:00, \r\n", "\r", - "Filter -> Patient Age:[35 - 65]&Patient Gender:M: 0%| | 0/396 [00:00 Patient Age:[35 - 65]&Patient Gender:M: 100%|█| 396/396 [00:00<00:00, \r\n" + "Filter -> Patient Age:[35 - 65]&Patient Gender:M: 0%| | 0/396 [00:00 Patient Age:[35 - 65]&Patient Gender:M: 100%|█| 396/396 [00:00<00:00, \r\n", "\r", "Filter -> Patient Age:[35 - 65]&Patient Gender:F: 0%| | 0/396 [00:00 Patient Age:[35 - 65]&Patient Gender:F: 100%|█| 396/396 [00:00<00:00, \r\n", @@ -316,18 +311,11 @@ "\r", "Filter -> Patient Age:[65 - 100]&Patient Gender:M: 100%|█| 396/396 [00:00<00:00,\r\n", "\r", - "Filter -> Patient Age:[65 - 100]&Patient Gender:F: 0%| | 0/396 [00:00 Patient Age:[65 - 100]&Patient Gender:F: 0%| | 0/396 [00:00 Patient Age:[65 - 100]&Patient Gender:F: 100%|█| 396/396 [00:00<00:00,\r\n", "\r", "Filter -> overall: 0%| | 0/396 [00:00 overall: 100%|████████████| 396/396 [00:00<00:00, 25361.03 examples/s]\r\n" + "Filter -> overall: 100%|████████████| 396/396 [00:00<00:00, 45328.98 examples/s]\r\n" ] }, { @@ -343,16 +331,13 @@ "output_type": "stream", "text": [ "\r", - "Flattening the indices: 100%|████████| 1000/1000 [00:51<00:00, 19.27 examples/s]\r", - "Flattening the indices: 100%|████████| 1000/1000 [00:51<00:00, 19.26 examples/s]\r\n", + "Flattening the indices: 100%|████████| 1000/1000 [00:50<00:00, 19.62 examples/s]\r", + "Flattening the indices: 100%|████████| 1000/1000 [00:50<00:00, 19.62 examples/s]\r\n", "\r", "Flattening the indices: 0%| | 0/1000 [00:00 Patient Gender:M: 0%| | 0/383 [00:00 Patient Gender:M: 100%|███| 383/383 [00:00<00:00, 42636.58 examples/s]\r\n" + "Map: 0%| | 0/383 [00:00 Patient Gender:F: 0%| | 0/383 [00:00 Patient Gender:F: 100%|███| 383/383 [00:00<00:00, 42604.92 examples/s]\r\n", + "Map: 100%|███████████████████████████| 383/383 [00:00<00:00, 1814.00 examples/s]\r", + "Map: 100%|███████████████████████████| 383/383 [00:00<00:00, 1778.88 examples/s]\r\n", "\r", - "Filter -> overall: 0%| | 0/383 [00:00 overall: 100%|████████████| 383/383 [00:00<00:00, 44897.11 examples/s]\r\n" + "Filter -> Patient Gender:M: 0%| | 0/383 [00:00 Patient Gender:M: 100%|███| 383/383 [00:00<00:00, 42006.65 examples/s]\r\n" ] }, { @@ -384,7 +367,10 @@ "output_type": "stream", "text": [ "\r", - "Filter -> Patient Age:[19 - 35]: 0%| | 0/383 [00:00 Patient Gender:F: 0%| | 0/383 [00:00 Patient Gender:F: 100%|███| 383/383 [00:00<00:00, 42493.35 examples/s]\r\n", + "\r", + "Filter -> overall: 0%| | 0/383 [00:00 Patient Age:[19 - 35]: 100%|█| 383/383 [00:00<00:00, 24012.95 examples\r\n", + "Filter -> overall: 100%|████████████| 383/383 [00:00<00:00, 44476.95 examples/s]\r\n", "\r", - "Filter -> Patient Age:[35 - 65]: 0%| | 0/383 [00:00 Patient Age:[35 - 65]: 100%|█| 383/383 [00:00<00:00, 23006.35 examples\r\n" + "Filter -> Patient Age:[19 - 35]: 0%| | 0/383 [00:00 Patient Age:[65 - 100]: 0%| | 0/383 [00:00 Patient Age:[65 - 100]: 100%|█| 383/383 [00:00<00:00, 24197.42 example\r\n" + "Filter -> Patient Age:[19 - 35]: 100%|█| 383/383 [00:00<00:00, 40546.67 examples\r\n", + "\r", + "Filter -> Patient Age:[35 - 65]: 0%| | 0/383 [00:00 Patient Age:[35 - 65]: 100%|█| 383/383 [00:00<00:00, 40422.19 examples\r\n", + "\r", + "Filter -> Patient Age:[65 - 100]: 0%| | 0/383 [00:00 Patient Age:[65 - 100]: 100%|█| 383/383 [00:00<00:00, 40312.64 example\r\n", "\r", "Filter -> Patient Age:[19 - 35]&Patient Gender:M: 0%| | 0/383 [00:00 Patient Age:[19 - 35]&Patient Gender:M: 100%|█| 383/383 [00:00<00:00, \r\n", "\r", - "Filter -> Patient Age:[19 - 35]&Patient Gender:F: 0%| | 0/383 [00:00 Patient Age:[19 - 35]&Patient Gender:F: 0%| | 0/383 [00:00 Patient Age:[19 - 35]&Patient Gender:F: 100%|█| 383/383 [00:00<00:00, \r\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "\r", - "Filter -> Patient Age:[19 - 35]&Patient Gender:F: 100%|█| 383/383 [00:00<00:00, \r\n", "\r", "Filter -> Patient Age:[35 - 65]&Patient Gender:M: 0%| | 0/383 [00:00 Patient Age:[35 - 65]&Patient Gender:M: 100%|█| 383/383 [00:00<00:00, \r\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Filter -> Patient Age:[35 - 65]&Patient Gender:M: 100%|█| 383/383 [00:00<00:00, \r\n", "\r", "Filter -> Patient Age:[35 - 65]&Patient Gender:F: 0%| | 0/383 [00:00 Patient Age:[35 - 65]&Patient Gender:F: 100%|█| 383/383 [00:00<00:00, \r\n" @@ -457,7 +441,7 @@ "output_type": "stream", "text": [ "\r", - "Filter -> overall: 100%|████████████| 383/383 [00:00<00:00, 45368.80 examples/s]\r\n" + "Filter -> overall: 100%|████████████| 383/383 [00:00<00:00, 45529.53 examples/s]\r\n" ] }, { @@ -473,7 +457,7 @@ "output_type": "stream", "text": [ "\r", - "Flattening the indices: 100%|████████| 1000/1000 [00:51<00:00, 19.51 examples/s]" + "Flattening the indices: 100%|████████| 1000/1000 [00:51<00:00, 19.39 examples/s]" ] }, { @@ -481,13 +465,13 @@ "output_type": "stream", "text": [ "\r", - "Flattening the indices: 100%|████████| 1000/1000 [00:51<00:00, 19.50 examples/s]\r\n", + "Flattening the indices: 100%|████████| 1000/1000 [00:51<00:00, 19.38 examples/s]\r\n", "\r", "Flattening the indices: 0%| | 0/1000 [00:00 Patient Gender:M: 0%| | 0/411 [00:00 Patient Gender:M: 100%|███| 411/411 [00:00<00:00, 44563.73 examples/s]\r\n", + "Filter -> Patient Gender:M: 100%|███| 411/411 [00:00<00:00, 43468.13 examples/s]\r\n", "\r", - "Filter -> Patient Gender:F: 0%| | 0/411 [00:00 Patient Gender:F: 0%| | 0/411 [00:00 Patient Gender:F: 100%|███| 411/411 [00:00<00:00, 42783.09 examples/s]\r\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "\r", - "Filter -> Patient Gender:F: 100%|███| 411/411 [00:00<00:00, 43622.12 examples/s]\r\n", "\r", "Filter -> overall: 0%| | 0/411 [00:00 overall: 100%|████████████| 411/411 [00:00<00:00, 45894.92 examples/s]\r\n" + "Filter -> overall: 100%|████████████| 411/411 [00:00<00:00, 44642.21 examples/s]\r\n" ] }, { @@ -529,7 +512,7 @@ "text": [ "\r", "Filter -> Patient Age:[19 - 35]: 0%| | 0/411 [00:00 Patient Age:[19 - 35]: 100%|█| 411/411 [00:00<00:00, 42074.07 examples\r\n", + "Filter -> Patient Age:[19 - 35]: 100%|█| 411/411 [00:00<00:00, 40946.77 examples\r\n", "\r", "Filter -> Patient Age:[35 - 65]: 0%| | 0/411 [00:00 Patient Age:[35 - 65]: 100%|█| 411/411 [00:00<00:00, 42672.94 examples\r\n", + "Filter -> Patient Age:[35 - 65]: 100%|█| 411/411 [00:00<00:00, 41775.33 examples\r\n", "\r", "Filter -> Patient Age:[65 - 100]: 0%| | 0/411 [00:00 Patient Age:[65 - 100]: 100%|█| 411/411 [00:00<00:00, 42232.81 example\r\n", - "\r", - "Filter -> Patient Age:[19 - 35]&Patient Gender:M: 0%| | 0/411 [00:00 Patient Age:[65 - 100]: 100%|█| 411/411 [00:00<00:00, 38797.69 example\r\n" ] }, { @@ -552,37 +533,40 @@ "output_type": "stream", "text": [ "\r", + "Filter -> Patient Age:[19 - 35]&Patient Gender:M: 0%| | 0/411 [00:00 Patient Age:[19 - 35]&Patient Gender:M: 100%|█| 411/411 [00:00<00:00, \r\n", "\r", "Filter -> Patient Age:[19 - 35]&Patient Gender:F: 0%| | 0/411 [00:00 Patient Age:[19 - 35]&Patient Gender:F: 100%|█| 411/411 [00:00<00:00, \r\n", "\r", - "Filter -> Patient Age:[35 - 65]&Patient Gender:M: 0%| | 0/411 [00:00 Patient Age:[35 - 65]&Patient Gender:M: 100%|█| 411/411 [00:00<00:00, \r\n" + "Filter -> Patient Age:[35 - 65]&Patient Gender:M: 0%| | 0/411 [00:00 Patient Age:[35 - 65]&Patient Gender:M: 100%|█| 411/411 [00:00<00:00, \r\n", "\r", "Filter -> Patient Age:[35 - 65]&Patient Gender:F: 0%| | 0/411 [00:00 Patient Age:[35 - 65]&Patient Gender:F: 100%|█| 411/411 [00:00<00:00, \r\n", "\r", - "Filter -> Patient Age:[65 - 100]&Patient Gender:M: 0%| | 0/411 [00:00 Patient Age:[65 - 100]&Patient Gender:M: 100%|█| 411/411 [00:00<00:00,\r\n" + "Filter -> Patient Age:[65 - 100]&Patient Gender:M: 0%| | 0/411 [00:00 Patient Age:[65 - 100]&Patient Gender:M: 100%|█| 411/411 [00:00<00:00,\r\n", "\r", "Filter -> Patient Age:[65 - 100]&Patient Gender:F: 0%| | 0/411 [00:00 Patient Age:[65 - 100]&Patient Gender:F: 100%|█| 411/411 [00:00<00:00,\r\n", "\r", "Filter -> overall: 0%| | 0/411 [00:00 overall: 100%|████████████| 411/411 [00:00<00:00, 47422.60 examples/s]\r\n" + "Filter -> overall: 100%|████████████| 411/411 [00:00<00:00, 47438.26 examples/s]\r\n" ] } ], @@ -630,10 +614,10 @@ "id": "03edf1c0", "metadata": { "execution": { - "iopub.execute_input": "2023-12-19T19:30:58.809719Z", - "iopub.status.busy": "2023-12-19T19:30:58.809124Z", - "iopub.status.idle": "2023-12-19T19:30:58.817339Z", - "shell.execute_reply": "2023-12-19T19:30:58.815914Z" + "iopub.execute_input": "2023-12-19T22:33:59.288623Z", + "iopub.status.busy": "2023-12-19T22:33:59.287880Z", + "iopub.status.idle": "2023-12-19T22:33:59.295931Z", + "shell.execute_reply": "2023-12-19T22:33:59.294681Z" } }, "outputs": [], @@ -655,10 +639,10 @@ "id": "6514120e", "metadata": { "execution": { - "iopub.execute_input": "2023-12-19T19:30:58.823228Z", - "iopub.status.busy": "2023-12-19T19:30:58.822720Z", - "iopub.status.idle": "2023-12-19T19:31:02.226167Z", - "shell.execute_reply": "2023-12-19T19:31:02.225157Z" + "iopub.execute_input": "2023-12-19T22:33:59.301865Z", + "iopub.status.busy": "2023-12-19T22:33:59.301230Z", + "iopub.status.idle": "2023-12-19T22:34:02.696538Z", + "shell.execute_reply": "2023-12-19T22:34:02.695891Z" } }, "outputs": [], @@ -702,17 +686,17 @@ "id": "5f624ed4", "metadata": { "execution": { - "iopub.execute_input": "2023-12-19T19:31:02.231227Z", - "iopub.status.busy": "2023-12-19T19:31:02.231028Z", - "iopub.status.idle": "2023-12-19T19:31:15.899234Z", - "shell.execute_reply": "2023-12-19T19:31:15.898590Z" + "iopub.execute_input": "2023-12-19T22:34:02.704636Z", + "iopub.status.busy": "2023-12-19T22:34:02.704423Z", + "iopub.status.idle": "2023-12-19T22:34:16.017323Z", + "shell.execute_reply": "2023-12-19T22:34:16.016688Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "cc502dd40d22491994b1f777025d0170", + "model_id": "9373c2e0d8d341dcba45cbcb12648fb4", "version_major": 2, "version_minor": 0 }, @@ -726,7 +710,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "d0855e42ae464c13bc77bfdf45b9a1b8", + "model_id": "8a408e146d974687bd808ec806200e98", "version_major": 2, "version_minor": 0 }, @@ -786,17 +770,17 @@ "id": "bff27cc1", "metadata": { "execution": { - "iopub.execute_input": "2023-12-19T19:31:15.906271Z", - "iopub.status.busy": "2023-12-19T19:31:15.905941Z", - "iopub.status.idle": "2023-12-19T19:31:16.128282Z", - "shell.execute_reply": "2023-12-19T19:31:16.127091Z" + "iopub.execute_input": "2023-12-19T22:34:16.023897Z", + "iopub.status.busy": "2023-12-19T22:34:16.023524Z", + "iopub.status.idle": "2023-12-19T22:34:16.241200Z", + "shell.execute_reply": "2023-12-19T22:34:16.240532Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "ba414d140e274eb99fa243548495972d", + "model_id": "6b59dd2683a74e9d8f23df1db7154fbf", "version_major": 2, "version_minor": 0 }, @@ -810,7 +794,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "92e5ed2fcbda473fbfd46a3ba2e5a467", + "model_id": "84eec996238e43349ea066fbf9114cf6", "version_major": 2, "version_minor": 0 }, @@ -824,7 +808,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "2ba6b7a22fd84f2d988580665b536257", + "model_id": "dedc21230b804d0d850f04e53ba3ada6", "version_major": 2, "version_minor": 0 }, @@ -944,17 +928,17 @@ "id": "8c38ef9e", "metadata": { "execution": { - "iopub.execute_input": "2023-12-19T19:31:16.133871Z", - "iopub.status.busy": "2023-12-19T19:31:16.133412Z", - "iopub.status.idle": "2023-12-19T19:31:16.629491Z", - "shell.execute_reply": "2023-12-19T19:31:16.628785Z" + "iopub.execute_input": "2023-12-19T22:34:16.246385Z", + "iopub.status.busy": "2023-12-19T22:34:16.246182Z", + "iopub.status.idle": "2023-12-19T22:34:16.740433Z", + "shell.execute_reply": "2023-12-19T22:34:16.739744Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "dbd4d21e0bc74b689fe5ae6705bbdc0a", + "model_id": "4070aba94ca743f88fae6c3c73778db9", "version_major": 2, "version_minor": 0 }, @@ -968,7 +952,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "3e6bdb6f706348bb8c2d616a4ac0d251", + "model_id": "1df5b904294f428ebc25d4ccec3e1a24", "version_major": 2, "version_minor": 0 }, @@ -982,7 +966,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "f012b1141b11446cadc73f655da956bf", + "model_id": "770a7e230aa2403488dc027bbcec2f9a", "version_major": 2, "version_minor": 0 }, @@ -996,7 +980,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "d81fea6fc9484d88b737954857008d8c", + "model_id": "ff6aa64a2b9d4cd89c82801a7c7e3fdf", "version_major": 2, "version_minor": 0 }, @@ -1010,7 +994,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "a5b8d136255c47a7b5c186868b5fcd25", + "model_id": "70ec85ae148547caa6e8bc3cca3ce09d", "version_major": 2, "version_minor": 0 }, @@ -1024,7 +1008,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "4ffe68e3a580427daae40759ea0f9e0c", + "model_id": "fda1272733154f13977e1967940816d9", "version_major": 2, "version_minor": 0 }, @@ -1038,7 +1022,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "4ed767c100ab45be994bfdf14b4eab6d", + "model_id": "c452a1315926481b8f3471086a8890d5", "version_major": 2, "version_minor": 0 }, @@ -1052,7 +1036,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "41187801fbcc4250950809a8f5fe7622", + "model_id": "1dc441d24c6b46af85e402a68955457c", "version_major": 2, "version_minor": 0 }, @@ -1066,7 +1050,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "eeb0097964644ce191866142bee65469", + "model_id": "2de2b2e0dd5744889a21eb933ec10716", "version_major": 2, "version_minor": 0 }, @@ -1080,7 +1064,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "edaae6c4bad3423bab46c5587bed7aff", + "model_id": "2d66f20811d84ddba30c6b13fecf3b8b", "version_major": 2, "version_minor": 0 }, @@ -1143,10 +1127,10 @@ "id": "3e674b7a", "metadata": { "execution": { - "iopub.execute_input": "2023-12-19T19:31:16.634447Z", - "iopub.status.busy": "2023-12-19T19:31:16.634230Z", - "iopub.status.idle": "2023-12-19T19:31:16.889083Z", - "shell.execute_reply": "2023-12-19T19:31:16.888412Z" + "iopub.execute_input": "2023-12-19T22:34:16.745343Z", + "iopub.status.busy": "2023-12-19T22:34:16.745103Z", + "iopub.status.idle": "2023-12-19T22:34:16.973205Z", + "shell.execute_reply": "2023-12-19T22:34:16.972554Z" } }, "outputs": [ @@ -2043,9 +2027,9 @@ } }, "text/html": [ - "
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@@ -671,49 +671,49 @@

Example 4. Sensitivity test experiment with different clinical shifts
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Example 5. Rolling window experiment with synthetic timestamps using biweekl

diff --git a/api/tutorials/nihcxr/monitor_api.ipynb b/api/tutorials/nihcxr/monitor_api.ipynb index 4ea510974..d84dd3286 100644 --- a/api/tutorials/nihcxr/monitor_api.ipynb +++ b/api/tutorials/nihcxr/monitor_api.ipynb @@ -22,17 +22,17 @@ "id": "8aa3302d", "metadata": { "execution": { - "iopub.execute_input": "2023-12-19T19:31:22.550401Z", - "iopub.status.busy": "2023-12-19T19:31:22.549839Z", - "iopub.status.idle": "2023-12-19T19:31:30.605597Z", - "shell.execute_reply": "2023-12-19T19:31:30.603651Z" + "iopub.execute_input": "2023-12-19T22:34:22.252387Z", + "iopub.status.busy": "2023-12-19T22:34:22.251573Z", + "iopub.status.idle": "2023-12-19T22:34:30.289082Z", + "shell.execute_reply": "2023-12-19T22:34:30.288337Z" } }, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 1, @@ -79,17 +79,17 @@ "id": "e11920db", "metadata": { "execution": { - "iopub.execute_input": "2023-12-19T19:31:30.613112Z", - "iopub.status.busy": "2023-12-19T19:31:30.612340Z", - "iopub.status.idle": "2023-12-19T19:31:31.235364Z", - "shell.execute_reply": "2023-12-19T19:31:31.234362Z" + "iopub.execute_input": "2023-12-19T22:34:30.296194Z", + "iopub.status.busy": "2023-12-19T22:34:30.295906Z", + "iopub.status.idle": "2023-12-19T22:34:30.915625Z", + "shell.execute_reply": "2023-12-19T22:34:30.914233Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "46e804cca0854e33ba29f34ed2e0b975", + "model_id": "9e2365758abe4c2cba7ad308a2b02260", "version_major": 2, "version_minor": 0 }, @@ -145,10 +145,10 @@ "id": "54a3523a", "metadata": { "execution": { - "iopub.execute_input": "2023-12-19T19:31:31.241025Z", - "iopub.status.busy": "2023-12-19T19:31:31.240643Z", - "iopub.status.idle": "2023-12-19T19:31:41.935056Z", - "shell.execute_reply": "2023-12-19T19:31:41.934392Z" + "iopub.execute_input": "2023-12-19T22:34:30.920619Z", + "iopub.status.busy": "2023-12-19T22:34:30.920076Z", + "iopub.status.idle": "2023-12-19T22:34:41.601690Z", + "shell.execute_reply": "2023-12-19T22:34:41.601013Z" } }, "outputs": [ @@ -213,10 +213,10 @@ "id": "40b5a90f", "metadata": { "execution": { - "iopub.execute_input": "2023-12-19T19:31:41.940756Z", - "iopub.status.busy": "2023-12-19T19:31:41.940466Z", - "iopub.status.idle": "2023-12-19T19:31:48.748539Z", - "shell.execute_reply": "2023-12-19T19:31:48.747697Z" + "iopub.execute_input": "2023-12-19T22:34:41.607701Z", + "iopub.status.busy": "2023-12-19T22:34:41.607329Z", + "iopub.status.idle": "2023-12-19T22:34:48.372208Z", + "shell.execute_reply": "2023-12-19T22:34:48.371516Z" } }, "outputs": [ @@ -271,17 +271,17 @@ "id": "9ba03fac", "metadata": { "execution": { - "iopub.execute_input": "2023-12-19T19:31:48.758101Z", - "iopub.status.busy": "2023-12-19T19:31:48.757727Z", - "iopub.status.idle": "2023-12-19T19:32:03.587067Z", - "shell.execute_reply": "2023-12-19T19:32:03.586354Z" + "iopub.execute_input": "2023-12-19T22:34:48.377609Z", + "iopub.status.busy": "2023-12-19T22:34:48.377256Z", + "iopub.status.idle": "2023-12-19T22:35:02.720249Z", + "shell.execute_reply": "2023-12-19T22:35:02.719181Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "8e7060dfa7d1462c9fe8cc702b4cdcd4", + "model_id": "f0b212f13df4435e87cc031143c1cbfc", "version_major": 2, "version_minor": 0 }, @@ -295,7 +295,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "68ee4fbafcba4dee97db7490d7be4eac", + "model_id": "9e88523b6f2545e1a9381174bd19ea97", "version_major": 2, "version_minor": 0 }, @@ -309,7 +309,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "f5923943f39f45c8b08e8a7ac2636e2d", + "model_id": "1f26b73e713942cc9881d5e44d3841f0", "version_major": 2, "version_minor": 0 }, @@ -323,7 +323,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "b346ee36c65c40dabebcc796298b2199", + "model_id": "f1fa11fb86f14a1281fc37442fe9c7e6", "version_major": 2, "version_minor": 0 }, @@ -337,7 +337,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "71e95656d7854d30b0652fffc55fb57b", + "model_id": "b7db996d421f45c6a600424baaa1d5ec", "version_major": 2, "version_minor": 0 }, @@ -351,7 +351,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - 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Graphics

-
+
@@ -3801,7 +3801,7 @@

Graphics

-
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Graphics

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diff --git a/api/tutorials/synthea/length_of_stay_report_periodic.html b/api/tutorials/synthea/length_of_stay_report_periodic.html index 83edd0d6e..7d97dfe1d 100644 --- a/api/tutorials/synthea/length_of_stay_report_periodic.html +++ b/api/tutorials/synthea/length_of_stay_report_periodic.html @@ -677,7 +677,7 @@

A quick glance of your most import
- 0.91 + 0.94 @@ -710,7 +710,7 @@

A quick glance of your most import
- 0.9 + 1.0 @@ -743,11 +743,11 @@

A quick glance of your most import
- 0.68 + 0.78 - ▼ + ▲ @@ -776,7 +776,7 @@

A quick glance of your most import
- 0.93 + 1.0 @@ -809,7 +809,7 @@

A quick glance of your most import
- 0.97 + 1.0 @@ -980,7 +980,7 @@

Graphics

-
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Graphics

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Graphics

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Graphics

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Graphics

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Quantitative Analysis
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Quantitative Analysis
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Quantitative Analysis
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Quantitative Analysis
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Quantitative Analysis
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Graphics

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Graphics

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Graphics

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Graphics

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Graphics

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Model Parameters

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Random_state

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Objective

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Colsample_bytree

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N_estimators

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Learning_rate

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N_estimators

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Eval_metric

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N_estimators

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Missing

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Min_child_weight

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Enable_categorical

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Gamma

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Gamma

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Gamma

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Learning_rate

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Colsample_bytree

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Missing

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Learning_rate

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Reg_lambda

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Objective

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Max_depth

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-

Eval_metric

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Eval_metric

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Min_child_weight

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Seed

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N_estimators

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Ethical Considerations

function generate_model_card_plot() { var model_card_plots = [] var overall_indices = [20, 21, 22, 23, 24] - var histories = JSON.parse("{\"0\": [\"0.8907563025210085\", \"1.0\", \"1.0\", \"1.0\", \"0.9880158526897856\"], \"1\": [\"0.9821428571428571\", \"0.9310590620637155\", \"1.0\", \"1.0\", \"1.0\"], \"2\": [\"0.8208955223880597\", \"0.731920694762269\", \"0.8426850825575278\", \"0.8608286275723958\", \"0.8223451934320134\"], \"3\": [\"0.8943089430894309\", \"0.842374421632282\", \"0.8932362828759461\", \"0.8090765221352141\", \"0.8184638991146056\"], \"4\": [\"0.9649827784156143\", \"0.9881424592480722\", \"0.9271337525858394\", \"0.8653006607189198\", \"0.8302038527466072\"], \"5\": [\"0.9038461538461539\", \"0.9150865766098234\", \"0.9082870772257372\", \"0.8357118692657074\", \"0.7348831846357723\"], \"6\": [\"0.9\", \"1.0\", \"1.0\", \"0.9086745376064163\", \"0.828451750272029\"], \"7\": [\"0.9310344827586207\", \"0.7897494937712568\", \"0.8732034606154833\", \"0.8225543126785403\", \"0.7419984686288204\"], \"8\": [\"0.9152542372881356\", \"0.8849163791574379\", \"0.8999944706422353\", \"0.8348382628735972\", \"0.8683776232269216\"], \"9\": [\"0.9685157421289355\", \"0.9163252458732778\", \"1.0\", \"0.9291101785796909\", \"0.9830693648760995\"], \"10\": [\"0.9166666666666666\", \"0.9352174971746042\", \"1.0\", \"1.0\", \"1.0\"], \"11\": [\"0.9863013698630136\", \"0.9163826950365944\", \"1.0\", \"1.0\", \"1.0\"], \"12\": [\"0.8888888888888888\", \"1.0\", \"1.0\", \"0.979193932264773\", \"0.9924238569900865\"], \"13\": [\"0.935064935064935\", \"0.897176412299387\", \"0.8366895341619429\", \"0.892718438334348\", \"0.8428129991536567\"], \"14\": [\"0.9743589743589743\", \"0.8745218955806155\", \"0.9839446244028153\", \"1.0\", \"1.0\"], \"15\": [\"0.8962264150943396\", \"0.8387316309976032\", \"0.9220820942432293\", \"0.7201166703885507\", \"0.6891709127206229\"], \"16\": [\"0.9344262295081968\", \"0.862901199134526\", \"0.8132047723856649\", \"0.8944937065377371\", \"0.9205028759616664\"], \"17\": [\"0.890625\", \"1.0\", \"1.0\", \"1.0\", \"0.9516431801207124\"], \"18\": [\"0.912\", \"0.9282486065384606\", \"1.0\", \"1.0\", \"1.0\"], \"19\": [\"0.9542410714285714\", \"0.8391307472945365\", \"0.861871218453203\", \"0.8445997198039747\", \"0.8120765760611559\"], \"20\": [\"0.9070796460176991\", \"0.886591473213573\", \"0.791949222268421\", \"0.8087503162499585\", \"0.9128423284988948\"], \"21\": [\"0.9626865671641791\", \"0.9212244674236073\", \"1.0\", \"1.0\", \"0.9037340616933736\"], \"22\": [\"0.8896551724137931\", \"0.8458745761391254\", \"0.7607926134165484\", \"0.6667993938585411\", \"0.6753374417087216\"], \"23\": [\"0.9247311827956989\", \"0.9630544398811139\", \"1.0\", \"1.0\", \"0.9254555959605683\"], \"24\": [\"0.9650063856960408\", \"0.9197140857265396\", \"0.8728212546001057\", \"0.9979788373833638\", \"0.9703193299741121\"]}"); + var histories = JSON.parse("{\"0\": [\"0.865546218487395\", \"0.9110266168194848\", \"0.9710350885766814\", \"0.923298252471693\", \"0.820221379413443\"], \"1\": [\"1.0\", \"0.8329775084800468\", \"0.8324122635428698\", \"0.8326066765321822\", \"0.8522291013231669\"], \"2\": [\"0.7681159420289855\", \"0.763681132183412\", \"0.7226001879092401\", \"0.7444053223981398\", \"0.6512582072414794\"], \"3\": [\"0.8688524590163934\", \"0.9075254807720297\", \"0.9799167019987514\", \"1.0\", \"0.9749641830482502\"], \"4\": [\"0.9510144927536232\", \"0.9397203435204348\", \"0.8837421461691282\", \"0.964141830725181\", \"1.0\"], \"5\": [\"0.9038461538461539\", \"0.764794664646071\", \"0.6430209723365414\", \"0.5386913753419003\", \"0.5532654285158163\"], \"6\": [\"0.896551724137931\", \"0.8801575449870345\", \"0.8882513615575618\", \"1.0\", \"0.9856587134851611\"], \"7\": [\"0.9285714285714286\", \"0.9301137770837963\", \"0.74858480154088\", \"0.8556739711696437\", \"0.8971594543005736\"], \"8\": [\"0.9122807017543859\", \"0.8350394943224642\", \"0.7253423179586007\", \"0.7669320968859538\", \"0.6708172392657945\"], \"9\": [\"0.9657738095238095\", \"0.9421423610770231\", \"0.924641133093329\", \"0.8358925806520754\", \"0.9320129165258605\"], \"10\": [\"0.9291338582677166\", \"1.0\", \"1.0\", \"0.9142658169079521\", \"0.8425563774253573\"], \"11\": [\"1.0\", \"0.897665729974571\", \"1.0\", \"0.8653938422670757\", \"0.9614429167450117\"], \"12\": [\"0.8902439024390244\", \"0.8130339983350626\", \"0.7535495034679031\", \"0.7185850979973456\", \"0.9001614105536506\"], \"13\": [\"0.9419354838709677\", \"0.9857020989846381\", \"0.9558090625958499\", \"0.9993299355690027\", \"0.9625270147387822\"], \"14\": [\"0.9780487804878049\", \"0.7887481675392372\", \"0.850321379433941\", \"0.7388724606423147\", \"0.7944827409032598\"], \"15\": [\"0.8585858585858586\", \"0.9788300654852401\", \"1.0\", \"0.9714210428506851\", \"1.0\"], \"16\": [\"0.9298245614035088\", \"0.7882842498535975\", \"0.7314776266368582\", \"0.7230192886110607\", \"0.6678639441875316\"], \"17\": [\"0.8412698412698413\", \"0.9016585321588075\", \"1.0\", \"0.9799381957459102\", \"1.0\"], \"18\": [\"0.8833333333333333\", \"0.8856142445674113\", \"0.9685816846205133\", \"0.8325758178437385\", \"0.8420244387747393\"], \"19\": [\"0.9581128747795414\", \"0.7879111284118243\", \"0.8674730934886363\", \"0.6921382331815268\", \"0.5440197774421514\"], \"20\": [\"0.8982300884955752\", \"0.8638135234641583\", \"0.8751088381943093\", \"0.8975168458012515\", \"0.9444525125063907\"], \"21\": [\"0.9692307692307692\", \"1.0\", \"1.0\", \"1.0\", \"1.0\"], \"22\": [\"0.8689655172413793\", \"0.885825130182628\", \"0.9624710731340196\", \"0.9813317184114776\", \"0.7829453737412231\"], \"23\": [\"0.9163636363636364\", \"0.9863156103089644\", \"1.0\", \"0.9500645458637769\", \"1.0\"], \"24\": [\"0.9686675180928055\", \"1.0\", \"1.0\", \"1.0\", \"1.0\"]}"); var thresholds = JSON.parse("{\"0\": \"0.7\", \"1\": \"0.7\", \"2\": \"0.7\", \"3\": \"0.7\", \"4\": \"0.7\", \"5\": \"0.7\", \"6\": \"0.7\", \"7\": \"0.7\", \"8\": \"0.7\", \"9\": \"0.7\", \"10\": \"0.7\", \"11\": \"0.7\", \"12\": \"0.7\", \"13\": \"0.7\", \"14\": \"0.7\", \"15\": \"0.7\", \"16\": \"0.7\", \"17\": \"0.7\", \"18\": \"0.7\", \"19\": \"0.7\", \"20\": \"0.7\", \"21\": \"0.7\", \"22\": \"0.7\", \"23\": \"0.7\", \"24\": \"0.7\"}"); var timestamps = JSON.parse("{\"0\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"1\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"2\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"3\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"4\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"5\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"6\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"7\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"8\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"9\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"10\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"11\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"12\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"13\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"14\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"15\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"16\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"17\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"18\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"19\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"20\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"21\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"22\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"23\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"24\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"]}"); @@ -2429,10 +2429,10 @@

Ethical Considerations

} } var slices_all = JSON.parse("{\"0\": [\"metric:Accuracy\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"1\": [\"metric:Precision\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"2\": [\"metric:Recall\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"3\": [\"metric:F1 Score\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"4\": [\"metric:AUROC\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"5\": [\"metric:Accuracy\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"6\": [\"metric:Precision\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"7\": [\"metric:Recall\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"8\": [\"metric:F1 Score\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"9\": [\"metric:AUROC\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"10\": [\"metric:Accuracy\", \"gender:M\", \"age:overall_age\"], \"11\": [\"metric:Precision\", \"gender:M\", \"age:overall_age\"], \"12\": [\"metric:Recall\", \"gender:M\", \"age:overall_age\"], \"13\": [\"metric:F1 Score\", \"gender:M\", \"age:overall_age\"], \"14\": [\"metric:AUROC\", \"gender:M\", \"age:overall_age\"], \"15\": [\"metric:Accuracy\", \"gender:F\", \"age:overall_age\"], \"16\": [\"metric:Precision\", \"gender:F\", \"age:overall_age\"], \"17\": [\"metric:Recall\", \"gender:F\", \"age:overall_age\"], \"18\": [\"metric:F1 Score\", \"gender:F\", \"age:overall_age\"], \"19\": [\"metric:AUROC\", \"gender:F\", \"age:overall_age\"], \"20\": [\"metric:Accuracy\", \"age:overall_age\", \"gender:overall_gender\"], \"21\": [\"metric:Precision\", \"age:overall_age\", \"gender:overall_gender\"], \"22\": [\"metric:Recall\", \"age:overall_age\", \"gender:overall_gender\"], \"23\": [\"metric:F1 Score\", \"age:overall_age\", \"gender:overall_gender\"], \"24\": [\"metric:AUROC\", \"age:overall_age\", \"gender:overall_gender\"]}"); - var histories_all = JSON.parse("{\"0\": [\"0.8907563025210085\", \"1.0\", \"1.0\", \"1.0\", \"0.9880158526897856\"], \"1\": [\"0.9821428571428571\", \"0.9310590620637155\", \"1.0\", \"1.0\", \"1.0\"], \"2\": [\"0.8208955223880597\", \"0.731920694762269\", \"0.8426850825575278\", \"0.8608286275723958\", \"0.8223451934320134\"], \"3\": [\"0.8943089430894309\", \"0.842374421632282\", \"0.8932362828759461\", \"0.8090765221352141\", \"0.8184638991146056\"], \"4\": [\"0.9649827784156143\", \"0.9881424592480722\", \"0.9271337525858394\", \"0.8653006607189198\", \"0.8302038527466072\"], \"5\": [\"0.9038461538461539\", \"0.9150865766098234\", \"0.9082870772257372\", \"0.8357118692657074\", \"0.7348831846357723\"], \"6\": [\"0.9\", \"1.0\", \"1.0\", \"0.9086745376064163\", \"0.828451750272029\"], \"7\": [\"0.9310344827586207\", \"0.7897494937712568\", \"0.8732034606154833\", \"0.8225543126785403\", \"0.7419984686288204\"], \"8\": [\"0.9152542372881356\", \"0.8849163791574379\", \"0.8999944706422353\", \"0.8348382628735972\", \"0.8683776232269216\"], \"9\": [\"0.9685157421289355\", \"0.9163252458732778\", \"1.0\", \"0.9291101785796909\", \"0.9830693648760995\"], \"10\": [\"0.9166666666666666\", \"0.9352174971746042\", \"1.0\", \"1.0\", \"1.0\"], \"11\": [\"0.9863013698630136\", \"0.9163826950365944\", \"1.0\", \"1.0\", \"1.0\"], \"12\": [\"0.8888888888888888\", \"1.0\", \"1.0\", \"0.979193932264773\", \"0.9924238569900865\"], \"13\": [\"0.935064935064935\", \"0.897176412299387\", \"0.8366895341619429\", \"0.892718438334348\", \"0.8428129991536567\"], \"14\": [\"0.9743589743589743\", \"0.8745218955806155\", \"0.9839446244028153\", \"1.0\", \"1.0\"], \"15\": [\"0.8962264150943396\", \"0.8387316309976032\", \"0.9220820942432293\", \"0.7201166703885507\", \"0.6891709127206229\"], \"16\": [\"0.9344262295081968\", \"0.862901199134526\", \"0.8132047723856649\", \"0.8944937065377371\", \"0.9205028759616664\"], \"17\": [\"0.890625\", \"1.0\", \"1.0\", \"1.0\", \"0.9516431801207124\"], \"18\": [\"0.912\", \"0.9282486065384606\", \"1.0\", \"1.0\", \"1.0\"], \"19\": [\"0.9542410714285714\", \"0.8391307472945365\", \"0.861871218453203\", \"0.8445997198039747\", \"0.8120765760611559\"], \"20\": [\"0.9070796460176991\", \"0.886591473213573\", \"0.791949222268421\", \"0.8087503162499585\", \"0.9128423284988948\"], \"21\": [\"0.9626865671641791\", \"0.9212244674236073\", \"1.0\", \"1.0\", \"0.9037340616933736\"], \"22\": [\"0.8896551724137931\", \"0.8458745761391254\", \"0.7607926134165484\", \"0.6667993938585411\", \"0.6753374417087216\"], \"23\": [\"0.9247311827956989\", \"0.9630544398811139\", \"1.0\", \"1.0\", \"0.9254555959605683\"], \"24\": [\"0.9650063856960408\", \"0.9197140857265396\", \"0.8728212546001057\", \"0.9979788373833638\", \"0.9703193299741121\"]}"); + var histories_all = JSON.parse("{\"0\": [\"0.865546218487395\", \"0.9110266168194848\", \"0.9710350885766814\", \"0.923298252471693\", \"0.820221379413443\"], \"1\": [\"1.0\", \"0.8329775084800468\", \"0.8324122635428698\", \"0.8326066765321822\", \"0.8522291013231669\"], \"2\": [\"0.7681159420289855\", \"0.763681132183412\", \"0.7226001879092401\", \"0.7444053223981398\", \"0.6512582072414794\"], \"3\": [\"0.8688524590163934\", \"0.9075254807720297\", \"0.9799167019987514\", \"1.0\", \"0.9749641830482502\"], \"4\": [\"0.9510144927536232\", \"0.9397203435204348\", \"0.8837421461691282\", \"0.964141830725181\", \"1.0\"], \"5\": [\"0.9038461538461539\", \"0.764794664646071\", \"0.6430209723365414\", \"0.5386913753419003\", \"0.5532654285158163\"], \"6\": [\"0.896551724137931\", \"0.8801575449870345\", \"0.8882513615575618\", \"1.0\", \"0.9856587134851611\"], \"7\": [\"0.9285714285714286\", \"0.9301137770837963\", \"0.74858480154088\", \"0.8556739711696437\", \"0.8971594543005736\"], \"8\": [\"0.9122807017543859\", \"0.8350394943224642\", \"0.7253423179586007\", \"0.7669320968859538\", \"0.6708172392657945\"], \"9\": [\"0.9657738095238095\", \"0.9421423610770231\", \"0.924641133093329\", \"0.8358925806520754\", \"0.9320129165258605\"], \"10\": [\"0.9291338582677166\", \"1.0\", \"1.0\", \"0.9142658169079521\", \"0.8425563774253573\"], \"11\": [\"1.0\", \"0.897665729974571\", \"1.0\", \"0.8653938422670757\", \"0.9614429167450117\"], \"12\": [\"0.8902439024390244\", \"0.8130339983350626\", \"0.7535495034679031\", \"0.7185850979973456\", \"0.9001614105536506\"], \"13\": [\"0.9419354838709677\", \"0.9857020989846381\", \"0.9558090625958499\", \"0.9993299355690027\", \"0.9625270147387822\"], \"14\": [\"0.9780487804878049\", \"0.7887481675392372\", \"0.850321379433941\", \"0.7388724606423147\", \"0.7944827409032598\"], \"15\": [\"0.8585858585858586\", \"0.9788300654852401\", \"1.0\", \"0.9714210428506851\", \"1.0\"], \"16\": [\"0.9298245614035088\", \"0.7882842498535975\", \"0.7314776266368582\", \"0.7230192886110607\", \"0.6678639441875316\"], \"17\": [\"0.8412698412698413\", \"0.9016585321588075\", \"1.0\", \"0.9799381957459102\", \"1.0\"], \"18\": [\"0.8833333333333333\", \"0.8856142445674113\", \"0.9685816846205133\", \"0.8325758178437385\", \"0.8420244387747393\"], \"19\": [\"0.9581128747795414\", \"0.7879111284118243\", \"0.8674730934886363\", \"0.6921382331815268\", \"0.5440197774421514\"], \"20\": [\"0.8982300884955752\", \"0.8638135234641583\", \"0.8751088381943093\", \"0.8975168458012515\", \"0.9444525125063907\"], \"21\": [\"0.9692307692307692\", \"1.0\", \"1.0\", \"1.0\", \"1.0\"], \"22\": [\"0.8689655172413793\", \"0.885825130182628\", \"0.9624710731340196\", \"0.9813317184114776\", \"0.7829453737412231\"], \"23\": [\"0.9163636363636364\", \"0.9863156103089644\", \"1.0\", \"0.9500645458637769\", \"1.0\"], \"24\": [\"0.9686675180928055\", \"1.0\", \"1.0\", \"1.0\", \"1.0\"]}"); var thresholds_all = JSON.parse("{\"0\": \"0.7\", \"1\": \"0.7\", \"2\": \"0.7\", \"3\": \"0.7\", \"4\": \"0.7\", \"5\": \"0.7\", \"6\": \"0.7\", \"7\": \"0.7\", \"8\": \"0.7\", \"9\": \"0.7\", \"10\": \"0.7\", \"11\": \"0.7\", \"12\": \"0.7\", \"13\": \"0.7\", \"14\": \"0.7\", \"15\": \"0.7\", \"16\": \"0.7\", \"17\": \"0.7\", \"18\": \"0.7\", \"19\": \"0.7\", \"20\": \"0.7\", \"21\": \"0.7\", \"22\": \"0.7\", \"23\": \"0.7\", \"24\": \"0.7\"}"); - var trends_all = JSON.parse("{\"0\": \"positive\", \"1\": \"positive\", \"2\": \"positive\", \"3\": \"negative\", \"4\": \"negative\", \"5\": \"negative\", \"6\": \"negative\", \"7\": \"negative\", \"8\": \"negative\", \"9\": \"neutral\", \"10\": \"positive\", \"11\": \"positive\", \"12\": \"positive\", \"13\": \"negative\", \"14\": \"positive\", \"15\": \"negative\", \"16\": \"neutral\", \"17\": \"positive\", \"18\": \"positive\", \"19\": \"negative\", \"20\": \"neutral\", \"21\": \"neutral\", \"22\": \"negative\", \"23\": \"neutral\", \"24\": \"neutral\"}"); - var passed_all = JSON.parse("{\"0\": true, \"1\": true, \"2\": true, \"3\": true, \"4\": true, \"5\": true, \"6\": true, \"7\": true, \"8\": true, \"9\": true, \"10\": true, \"11\": true, \"12\": true, \"13\": true, \"14\": true, \"15\": false, \"16\": true, \"17\": true, \"18\": true, \"19\": true, \"20\": true, \"21\": true, \"22\": false, \"23\": true, \"24\": true}"); + var trends_all = JSON.parse("{\"0\": \"neutral\", \"1\": \"negative\", \"2\": \"negative\", \"3\": \"positive\", \"4\": \"positive\", \"5\": \"negative\", \"6\": \"positive\", \"7\": \"negative\", \"8\": \"negative\", \"9\": \"negative\", \"10\": \"negative\", \"11\": \"negative\", \"12\": \"neutral\", \"13\": \"neutral\", \"14\": \"negative\", \"15\": \"positive\", \"16\": \"negative\", \"17\": \"positive\", \"18\": \"negative\", \"19\": \"negative\", \"20\": \"positive\", \"21\": \"neutral\", \"22\": \"neutral\", \"23\": \"positive\", \"24\": \"neutral\"}"); + var passed_all = JSON.parse("{\"0\": true, \"1\": true, \"2\": false, \"3\": true, \"4\": true, \"5\": false, \"6\": true, \"7\": true, \"8\": false, \"9\": true, \"10\": true, \"11\": true, \"12\": true, \"13\": true, \"14\": true, \"15\": true, \"16\": false, \"17\": true, \"18\": true, \"19\": false, \"20\": true, \"21\": true, \"22\": true, \"23\": true, \"24\": true}"); var names_all = JSON.parse("{\"0\": \"Accuracy\", \"1\": \"Precision\", \"2\": \"Recall\", \"3\": \"F1 Score\", \"4\": \"AUROC\", \"5\": \"Accuracy\", \"6\": \"Precision\", \"7\": \"Recall\", \"8\": \"F1 Score\", \"9\": \"AUROC\", \"10\": \"Accuracy\", \"11\": \"Precision\", \"12\": \"Recall\", \"13\": \"F1 Score\", \"14\": \"AUROC\", \"15\": \"Accuracy\", \"16\": \"Precision\", \"17\": \"Recall\", \"18\": \"F1 Score\", \"19\": \"AUROC\", \"20\": \"Accuracy\", \"21\": \"Precision\", \"22\": \"Recall\", \"23\": \"F1 Score\", \"24\": \"AUROC\"}"); var timestamps_all = JSON.parse("{\"0\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"1\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"2\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"3\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"4\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"5\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"6\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"7\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"8\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"9\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"10\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"11\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"12\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"13\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"14\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"15\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"16\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"17\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"18\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"19\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"20\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"21\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"22\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"23\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"24\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"]}"); @@ -2720,10 +2720,10 @@

Ethical Considerations

} } var slices_all = JSON.parse("{\"0\": [\"metric:Accuracy\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"1\": [\"metric:Precision\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"2\": [\"metric:Recall\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"3\": [\"metric:F1 Score\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"4\": [\"metric:AUROC\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"5\": [\"metric:Accuracy\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"6\": [\"metric:Precision\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"7\": [\"metric:Recall\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"8\": [\"metric:F1 Score\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"9\": [\"metric:AUROC\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"10\": [\"metric:Accuracy\", \"gender:M\", \"age:overall_age\"], \"11\": [\"metric:Precision\", \"gender:M\", \"age:overall_age\"], \"12\": [\"metric:Recall\", \"gender:M\", \"age:overall_age\"], \"13\": [\"metric:F1 Score\", \"gender:M\", \"age:overall_age\"], \"14\": [\"metric:AUROC\", \"gender:M\", \"age:overall_age\"], \"15\": [\"metric:Accuracy\", \"gender:F\", \"age:overall_age\"], \"16\": [\"metric:Precision\", \"gender:F\", \"age:overall_age\"], \"17\": [\"metric:Recall\", \"gender:F\", \"age:overall_age\"], \"18\": [\"metric:F1 Score\", \"gender:F\", \"age:overall_age\"], \"19\": [\"metric:AUROC\", \"gender:F\", \"age:overall_age\"], \"20\": [\"metric:Accuracy\", \"age:overall_age\", \"gender:overall_gender\"], \"21\": [\"metric:Precision\", \"age:overall_age\", \"gender:overall_gender\"], \"22\": [\"metric:Recall\", \"age:overall_age\", \"gender:overall_gender\"], \"23\": [\"metric:F1 Score\", \"age:overall_age\", \"gender:overall_gender\"], \"24\": [\"metric:AUROC\", \"age:overall_age\", \"gender:overall_gender\"]}"); - var histories_all = JSON.parse("{\"0\": [\"0.8907563025210085\", \"1.0\", \"1.0\", \"1.0\", \"0.9880158526897856\"], \"1\": [\"0.9821428571428571\", \"0.9310590620637155\", \"1.0\", \"1.0\", \"1.0\"], \"2\": [\"0.8208955223880597\", \"0.731920694762269\", \"0.8426850825575278\", \"0.8608286275723958\", \"0.8223451934320134\"], \"3\": [\"0.8943089430894309\", \"0.842374421632282\", \"0.8932362828759461\", \"0.8090765221352141\", \"0.8184638991146056\"], \"4\": [\"0.9649827784156143\", \"0.9881424592480722\", \"0.9271337525858394\", \"0.8653006607189198\", \"0.8302038527466072\"], \"5\": [\"0.9038461538461539\", \"0.9150865766098234\", \"0.9082870772257372\", \"0.8357118692657074\", \"0.7348831846357723\"], \"6\": [\"0.9\", \"1.0\", \"1.0\", \"0.9086745376064163\", \"0.828451750272029\"], \"7\": [\"0.9310344827586207\", \"0.7897494937712568\", \"0.8732034606154833\", \"0.8225543126785403\", \"0.7419984686288204\"], \"8\": [\"0.9152542372881356\", \"0.8849163791574379\", \"0.8999944706422353\", \"0.8348382628735972\", \"0.8683776232269216\"], \"9\": [\"0.9685157421289355\", \"0.9163252458732778\", \"1.0\", \"0.9291101785796909\", \"0.9830693648760995\"], \"10\": [\"0.9166666666666666\", \"0.9352174971746042\", \"1.0\", \"1.0\", \"1.0\"], \"11\": [\"0.9863013698630136\", \"0.9163826950365944\", \"1.0\", \"1.0\", \"1.0\"], \"12\": [\"0.8888888888888888\", \"1.0\", \"1.0\", \"0.979193932264773\", \"0.9924238569900865\"], \"13\": [\"0.935064935064935\", \"0.897176412299387\", \"0.8366895341619429\", \"0.892718438334348\", \"0.8428129991536567\"], \"14\": [\"0.9743589743589743\", \"0.8745218955806155\", \"0.9839446244028153\", \"1.0\", \"1.0\"], \"15\": [\"0.8962264150943396\", \"0.8387316309976032\", \"0.9220820942432293\", \"0.7201166703885507\", \"0.6891709127206229\"], \"16\": [\"0.9344262295081968\", \"0.862901199134526\", \"0.8132047723856649\", \"0.8944937065377371\", \"0.9205028759616664\"], \"17\": [\"0.890625\", \"1.0\", \"1.0\", \"1.0\", \"0.9516431801207124\"], \"18\": [\"0.912\", \"0.9282486065384606\", \"1.0\", \"1.0\", \"1.0\"], \"19\": [\"0.9542410714285714\", \"0.8391307472945365\", \"0.861871218453203\", \"0.8445997198039747\", \"0.8120765760611559\"], \"20\": [\"0.9070796460176991\", \"0.886591473213573\", \"0.791949222268421\", \"0.8087503162499585\", \"0.9128423284988948\"], \"21\": [\"0.9626865671641791\", \"0.9212244674236073\", \"1.0\", \"1.0\", \"0.9037340616933736\"], \"22\": [\"0.8896551724137931\", \"0.8458745761391254\", \"0.7607926134165484\", \"0.6667993938585411\", \"0.6753374417087216\"], \"23\": [\"0.9247311827956989\", \"0.9630544398811139\", \"1.0\", \"1.0\", \"0.9254555959605683\"], \"24\": [\"0.9650063856960408\", \"0.9197140857265396\", \"0.8728212546001057\", \"0.9979788373833638\", \"0.9703193299741121\"]}"); + var histories_all = JSON.parse("{\"0\": [\"0.865546218487395\", \"0.9110266168194848\", \"0.9710350885766814\", \"0.923298252471693\", \"0.820221379413443\"], \"1\": [\"1.0\", \"0.8329775084800468\", \"0.8324122635428698\", \"0.8326066765321822\", \"0.8522291013231669\"], \"2\": [\"0.7681159420289855\", \"0.763681132183412\", \"0.7226001879092401\", \"0.7444053223981398\", \"0.6512582072414794\"], \"3\": [\"0.8688524590163934\", \"0.9075254807720297\", \"0.9799167019987514\", \"1.0\", \"0.9749641830482502\"], \"4\": [\"0.9510144927536232\", \"0.9397203435204348\", \"0.8837421461691282\", \"0.964141830725181\", \"1.0\"], \"5\": [\"0.9038461538461539\", \"0.764794664646071\", \"0.6430209723365414\", \"0.5386913753419003\", \"0.5532654285158163\"], \"6\": [\"0.896551724137931\", \"0.8801575449870345\", \"0.8882513615575618\", \"1.0\", \"0.9856587134851611\"], \"7\": [\"0.9285714285714286\", \"0.9301137770837963\", \"0.74858480154088\", \"0.8556739711696437\", \"0.8971594543005736\"], \"8\": [\"0.9122807017543859\", \"0.8350394943224642\", \"0.7253423179586007\", \"0.7669320968859538\", \"0.6708172392657945\"], \"9\": [\"0.9657738095238095\", \"0.9421423610770231\", \"0.924641133093329\", \"0.8358925806520754\", \"0.9320129165258605\"], \"10\": [\"0.9291338582677166\", \"1.0\", \"1.0\", \"0.9142658169079521\", \"0.8425563774253573\"], \"11\": [\"1.0\", \"0.897665729974571\", \"1.0\", \"0.8653938422670757\", \"0.9614429167450117\"], \"12\": [\"0.8902439024390244\", \"0.8130339983350626\", \"0.7535495034679031\", \"0.7185850979973456\", \"0.9001614105536506\"], \"13\": [\"0.9419354838709677\", \"0.9857020989846381\", \"0.9558090625958499\", \"0.9993299355690027\", \"0.9625270147387822\"], \"14\": [\"0.9780487804878049\", \"0.7887481675392372\", \"0.850321379433941\", \"0.7388724606423147\", \"0.7944827409032598\"], \"15\": [\"0.8585858585858586\", \"0.9788300654852401\", \"1.0\", \"0.9714210428506851\", \"1.0\"], \"16\": [\"0.9298245614035088\", \"0.7882842498535975\", \"0.7314776266368582\", \"0.7230192886110607\", \"0.6678639441875316\"], \"17\": [\"0.8412698412698413\", \"0.9016585321588075\", \"1.0\", \"0.9799381957459102\", \"1.0\"], \"18\": [\"0.8833333333333333\", \"0.8856142445674113\", \"0.9685816846205133\", \"0.8325758178437385\", \"0.8420244387747393\"], \"19\": [\"0.9581128747795414\", \"0.7879111284118243\", \"0.8674730934886363\", \"0.6921382331815268\", \"0.5440197774421514\"], \"20\": [\"0.8982300884955752\", \"0.8638135234641583\", \"0.8751088381943093\", \"0.8975168458012515\", \"0.9444525125063907\"], \"21\": [\"0.9692307692307692\", \"1.0\", \"1.0\", \"1.0\", \"1.0\"], \"22\": [\"0.8689655172413793\", \"0.885825130182628\", \"0.9624710731340196\", \"0.9813317184114776\", \"0.7829453737412231\"], \"23\": [\"0.9163636363636364\", \"0.9863156103089644\", \"1.0\", \"0.9500645458637769\", \"1.0\"], \"24\": [\"0.9686675180928055\", \"1.0\", \"1.0\", \"1.0\", \"1.0\"]}"); var thresholds_all = JSON.parse("{\"0\": \"0.7\", \"1\": \"0.7\", \"2\": \"0.7\", \"3\": \"0.7\", \"4\": \"0.7\", \"5\": \"0.7\", \"6\": \"0.7\", \"7\": \"0.7\", \"8\": \"0.7\", \"9\": \"0.7\", \"10\": \"0.7\", \"11\": \"0.7\", \"12\": \"0.7\", \"13\": \"0.7\", \"14\": \"0.7\", \"15\": \"0.7\", \"16\": \"0.7\", \"17\": \"0.7\", \"18\": \"0.7\", \"19\": \"0.7\", \"20\": \"0.7\", \"21\": \"0.7\", \"22\": \"0.7\", \"23\": \"0.7\", \"24\": \"0.7\"}"); - var trends_all = JSON.parse("{\"0\": \"positive\", \"1\": \"positive\", \"2\": \"positive\", \"3\": \"negative\", \"4\": \"negative\", \"5\": \"negative\", \"6\": \"negative\", \"7\": \"negative\", \"8\": \"negative\", \"9\": \"neutral\", \"10\": \"positive\", \"11\": \"positive\", \"12\": \"positive\", \"13\": \"negative\", \"14\": \"positive\", \"15\": \"negative\", \"16\": \"neutral\", \"17\": \"positive\", \"18\": \"positive\", \"19\": \"negative\", \"20\": \"neutral\", \"21\": \"neutral\", \"22\": \"negative\", \"23\": \"neutral\", \"24\": \"neutral\"}"); - var passed_all = JSON.parse("{\"0\": true, \"1\": true, \"2\": true, \"3\": true, \"4\": true, \"5\": true, \"6\": true, \"7\": true, \"8\": true, \"9\": true, \"10\": true, \"11\": true, \"12\": true, \"13\": true, \"14\": true, \"15\": false, \"16\": true, \"17\": true, \"18\": true, \"19\": true, \"20\": true, \"21\": true, \"22\": false, \"23\": true, \"24\": true}"); + var trends_all = JSON.parse("{\"0\": \"neutral\", \"1\": \"negative\", \"2\": \"negative\", \"3\": \"positive\", \"4\": \"positive\", \"5\": \"negative\", \"6\": \"positive\", \"7\": \"negative\", \"8\": \"negative\", \"9\": \"negative\", \"10\": \"negative\", \"11\": \"negative\", \"12\": \"neutral\", \"13\": \"neutral\", \"14\": \"negative\", \"15\": \"positive\", \"16\": \"negative\", \"17\": \"positive\", \"18\": \"negative\", \"19\": \"negative\", \"20\": \"positive\", \"21\": \"neutral\", \"22\": \"neutral\", \"23\": \"positive\", \"24\": \"neutral\"}"); + var passed_all = JSON.parse("{\"0\": true, \"1\": true, \"2\": false, \"3\": true, \"4\": true, \"5\": false, \"6\": true, \"7\": true, \"8\": false, \"9\": true, \"10\": true, \"11\": true, \"12\": true, \"13\": true, \"14\": true, \"15\": true, \"16\": false, \"17\": true, \"18\": true, \"19\": false, \"20\": true, \"21\": true, \"22\": true, \"23\": true, \"24\": true}"); var names_all = JSON.parse("{\"0\": \"Accuracy\", \"1\": \"Precision\", \"2\": \"Recall\", \"3\": \"F1 Score\", \"4\": \"AUROC\", \"5\": \"Accuracy\", \"6\": \"Precision\", \"7\": \"Recall\", \"8\": \"F1 Score\", \"9\": \"AUROC\", \"10\": \"Accuracy\", \"11\": \"Precision\", \"12\": \"Recall\", \"13\": \"F1 Score\", \"14\": \"AUROC\", \"15\": \"Accuracy\", \"16\": \"Precision\", \"17\": \"Recall\", \"18\": \"F1 Score\", \"19\": \"AUROC\", \"20\": \"Accuracy\", \"21\": \"Precision\", \"22\": \"Recall\", \"23\": \"F1 Score\", \"24\": \"AUROC\"}"); var timestamps_all = JSON.parse("{\"0\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"1\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"2\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"3\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"4\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"5\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"6\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"7\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"8\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"9\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"10\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"11\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"12\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"13\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"14\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"15\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"16\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"17\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"18\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"19\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"20\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"21\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"22\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"23\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"24\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"]}"); diff --git a/api/tutorials/synthea/los_prediction.html b/api/tutorials/synthea/los_prediction.html index 197bf2f37..783d9ff22 100644 --- a/api/tutorials/synthea/los_prediction.html +++ b/api/tutorials/synthea/los_prediction.html @@ -677,17 +677,17 @@

Compute length of stay (labels) 
-2023-12-19 14:32:13,413 INFO cycquery.orm    - Database setup, ready to run queries!
-2023-12-19 14:32:18,601 INFO cycquery.orm    - Query returned successfully!
-2023-12-19 14:32:18,602 INFO cycquery.utils.profile - Finished executing function run_query in 3.866833 s
-2023-12-19 14:32:20,410 INFO cycquery.orm    - Query returned successfully!
-2023-12-19 14:32:20,412 INFO cycquery.utils.profile - Finished executing function run_query in 1.808322 s
-2023-12-19 14:32:21,969 INFO cycquery.orm    - Query returned successfully!
-2023-12-19 14:32:21,970 INFO cycquery.utils.profile - Finished executing function run_query in 0.395373 s
-2023-12-19 14:32:22,461 INFO cycquery.orm    - Query returned successfully!
-2023-12-19 14:32:22,462 INFO cycquery.utils.profile - Finished executing function run_query in 0.487607 s
-2023-12-19 14:32:22,565 INFO cycquery.orm    - Query returned successfully!
-2023-12-19 14:32:22,566 INFO cycquery.utils.profile - Finished executing function run_query in 0.102961 s
+2023-12-19 17:35:12,894 INFO cycquery.orm    - Database setup, ready to run queries!
+2023-12-19 17:35:16,811 INFO cycquery.orm    - Query returned successfully!
+2023-12-19 17:35:16,812 INFO cycquery.utils.profile - Finished executing function run_query in 3.051921 s
+2023-12-19 17:35:18,703 INFO cycquery.orm    - Query returned successfully!
+2023-12-19 17:35:18,704 INFO cycquery.utils.profile - Finished executing function run_query in 1.891131 s
+2023-12-19 17:35:20,059 INFO cycquery.orm    - Query returned successfully!
+2023-12-19 17:35:20,060 INFO cycquery.utils.profile - Finished executing function run_query in 0.123429 s
+2023-12-19 17:35:20,270 INFO cycquery.orm    - Query returned successfully!
+2023-12-19 17:35:20,271 INFO cycquery.utils.profile - Finished executing function run_query in 0.206623 s
+2023-12-19 17:35:20,354 INFO cycquery.orm    - Query returned successfully!
+2023-12-19 17:35:20,355 INFO cycquery.utils.profile - Finished executing function run_query in 0.083895 s

@@ -740,9 +740,9 @@

Drop NaNs based on the

-
+
@@ -1304,12 +1304,12 @@

Training 

-2023-12-19 14:32:27,945 INFO cyclops.models.wrappers.sk_model - Best reg_lambda: 0
-2023-12-19 14:32:27,946 INFO cyclops.models.wrappers.sk_model - Best n_estimators: 100
-2023-12-19 14:32:27,947 INFO cyclops.models.wrappers.sk_model - Best max_depth: 2
-2023-12-19 14:32:27,947 INFO cyclops.models.wrappers.sk_model - Best learning_rate: 0.1
-2023-12-19 14:32:27,948 INFO cyclops.models.wrappers.sk_model - Best gamma: 1
-2023-12-19 14:32:27,948 INFO cyclops.models.wrappers.sk_model - Best colsample_bytree: 0.7
+2023-12-19 17:35:31,318 INFO cyclops.models.wrappers.sk_model - Best reg_lambda: 1
+2023-12-19 17:35:31,319 INFO cyclops.models.wrappers.sk_model - Best n_estimators: 500
+2023-12-19 17:35:31,320 INFO cyclops.models.wrappers.sk_model - Best max_depth: 2
+2023-12-19 17:35:31,321 INFO cyclops.models.wrappers.sk_model - Best learning_rate: 0.01
+2023-12-19 17:35:31,322 INFO cyclops.models.wrappers.sk_model - Best gamma: 1
+2023-12-19 17:35:31,322 INFO cyclops.models.wrappers.sk_model - Best colsample_bytree: 0.8
@@ -1319,24 +1319,24 @@

Training 
XGBClassifier(base_score=None, booster=None, callbacks=None,
               colsample_bylevel=None, colsample_bynode=None,
-              colsample_bytree=0.7, early_stopping_rounds=None,
+              colsample_bytree=0.8, early_stopping_rounds=None,
               enable_categorical=False, eval_metric='logloss',
               feature_types=None, gamma=1, gpu_id=None, grow_policy=None,
               importance_type=None, interaction_constraints=None,
-              learning_rate=0.1, max_bin=None, max_cat_threshold=None,
+              learning_rate=0.01, max_bin=None, max_cat_threshold=None,
               max_cat_to_onehot=None, max_delta_step=None, max_depth=2,
               max_leaves=None, min_child_weight=3, missing=nan,
-              monotone_constraints=None, n_estimators=100, n_jobs=None,
+              monotone_constraints=None, n_estimators=500, n_jobs=None,
               num_parallel_tree=None, predictor=None, random_state=123, ...)
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.

@@ -1353,7 +1353,7 @@

Training 

-{'objective': 'binary:logistic', 'use_label_encoder': None, 'base_score': None, 'booster': None, 'callbacks': None, 'colsample_bylevel': None, 'colsample_bynode': None, 'colsample_bytree': 0.7, 'early_stopping_rounds': None, 'enable_categorical': False, 'eval_metric': 'logloss', 'feature_types': None, 'gamma': 1, 'gpu_id': None, 'grow_policy': None, 'importance_type': None, 'interaction_constraints': None, 'learning_rate': 0.1, 'max_bin': None, 'max_cat_threshold': None, 'max_cat_to_onehot': None, 'max_delta_step': None, 'max_depth': 2, 'max_leaves': None, 'min_child_weight': 3, 'missing': nan, 'monotone_constraints': None, 'n_estimators': 100, 'n_jobs': None, 'num_parallel_tree': None, 'predictor': None, 'random_state': 123, 'reg_alpha': None, 'reg_lambda': 0, 'sampling_method': None, 'scale_pos_weight': None, 'subsample': None, 'tree_method': None, 'validate_parameters': None, 'verbosity': None, 'seed': 123}
+{'objective': 'binary:logistic', 'use_label_encoder': None, 'base_score': None, 'booster': None, 'callbacks': None, 'colsample_bylevel': None, 'colsample_bynode': None, 'colsample_bytree': 0.8, 'early_stopping_rounds': None, 'enable_categorical': False, 'eval_metric': 'logloss', 'feature_types': None, 'gamma': 1, 'gpu_id': None, 'grow_policy': None, 'importance_type': None, 'interaction_constraints': None, 'learning_rate': 0.01, 'max_bin': None, 'max_cat_threshold': None, 'max_cat_to_onehot': None, 'max_delta_step': None, 'max_depth': 2, 'max_leaves': None, 'min_child_weight': 3, 'missing': nan, 'monotone_constraints': None, 'n_estimators': 500, 'n_jobs': None, 'num_parallel_tree': None, 'predictor': None, 'random_state': 123, 'reg_alpha': None, 'reg_lambda': 1, 'sampling_method': None, 'scale_pos_weight': None, 'subsample': None, 'tree_method': None, 'validate_parameters': None, 'verbosity': None, 'seed': 123}

Log the model parameters to the report.

@@ -1389,7 +1389,7 @@

Prediction

-
+

@@ -1518,85 +1518,85 @@

Evaluation

-
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+

Log the performance metrics to the report.

We can add a performance metric to the model card using the log_performance_metric method, which expects a dictionary where the keys are in the following format: slice_name/metric_name. For instance, overall/accuracy.

@@ -1700,9 +1700,9 @@

Evaluation
-
diff --git a/api/tutorials/synthea/los_prediction.ipynb b/api/tutorials/synthea/los_prediction.ipynb index 1de6f07eb..9f0f0f1d7 100644 --- a/api/tutorials/synthea/los_prediction.ipynb +++ b/api/tutorials/synthea/los_prediction.ipynb @@ -33,10 +33,10 @@ "id": "53009e6b", "metadata": { "execution": { - "iopub.execute_input": "2023-12-19T19:32:08.602168Z", - "iopub.status.busy": "2023-12-19T19:32:08.601199Z", - "iopub.status.idle": "2023-12-19T19:32:12.684781Z", - "shell.execute_reply": "2023-12-19T19:32:12.684076Z" + "iopub.execute_input": "2023-12-19T22:35:08.071900Z", + "iopub.status.busy": "2023-12-19T22:35:08.071010Z", + "iopub.status.idle": "2023-12-19T22:35:12.249433Z", + "shell.execute_reply": "2023-12-19T22:35:12.248666Z" } }, "outputs": [], @@ -96,10 +96,10 @@ "id": "afae58a8-5708-4e05-8695-25ba3ce1a71f", "metadata": { "execution": { - "iopub.execute_input": "2023-12-19T19:32:12.690051Z", - "iopub.status.busy": "2023-12-19T19:32:12.689683Z", - "iopub.status.idle": "2023-12-19T19:32:12.693112Z", - "shell.execute_reply": "2023-12-19T19:32:12.692549Z" + "iopub.execute_input": "2023-12-19T22:35:12.254483Z", + "iopub.status.busy": "2023-12-19T22:35:12.254099Z", + "iopub.status.idle": "2023-12-19T22:35:12.257752Z", + "shell.execute_reply": "2023-12-19T22:35:12.257159Z" }, "tags": [] }, @@ -122,10 +122,10 @@ "id": "739b109a-011b-4e6e-a3de-964edeffddbd", "metadata": { "execution": { - "iopub.execute_input": "2023-12-19T19:32:12.700702Z", - "iopub.status.busy": "2023-12-19T19:32:12.700463Z", - "iopub.status.idle": "2023-12-19T19:32:12.704949Z", - "shell.execute_reply": "2023-12-19T19:32:12.704025Z" + "iopub.execute_input": "2023-12-19T22:35:12.262477Z", + "iopub.status.busy": "2023-12-19T22:35:12.262300Z", + "iopub.status.idle": "2023-12-19T22:35:12.265398Z", + "shell.execute_reply": "2023-12-19T22:35:12.264824Z" }, "tags": [] }, @@ -156,10 +156,10 @@ "id": "e497df9f-0f3d-4e9c-845c-539627a37f67", "metadata": { "execution": { - "iopub.execute_input": "2023-12-19T19:32:12.709859Z", - "iopub.status.busy": "2023-12-19T19:32:12.709461Z", - "iopub.status.idle": "2023-12-19T19:32:22.605886Z", - "shell.execute_reply": "2023-12-19T19:32:22.604509Z" + "iopub.execute_input": "2023-12-19T22:35:12.270107Z", + "iopub.status.busy": "2023-12-19T22:35:12.269926Z", + "iopub.status.idle": "2023-12-19T22:35:20.397465Z", + "shell.execute_reply": "2023-12-19T22:35:20.396750Z" }, "tags": [] }, @@ -168,77 +168,77 @@ "name": "stderr", "output_type": "stream", "text": [ - "2023-12-19 14:32:13,413 \u001b[1;37mINFO\u001b[0m cycquery.orm - Database setup, ready to run queries!\n" + "2023-12-19 17:35:12,894 \u001b[1;37mINFO\u001b[0m cycquery.orm - Database setup, ready to run queries!\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2023-12-19 14:32:18,601 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" + "2023-12-19 17:35:16,811 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2023-12-19 14:32:18,602 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 3.866833 s\n" + "2023-12-19 17:35:16,812 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 3.051921 s\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2023-12-19 14:32:20,410 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" + "2023-12-19 17:35:18,703 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2023-12-19 14:32:20,412 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 1.808322 s\n" + "2023-12-19 17:35:18,704 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 1.891131 s\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2023-12-19 14:32:21,969 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" + "2023-12-19 17:35:20,059 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2023-12-19 14:32:21,970 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 0.395373 s\n" + "2023-12-19 17:35:20,060 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 0.123429 s\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2023-12-19 14:32:22,461 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" + "2023-12-19 17:35:20,270 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2023-12-19 14:32:22,462 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 0.487607 s\n" + "2023-12-19 17:35:20,271 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 0.206623 s\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2023-12-19 14:32:22,565 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" + "2023-12-19 17:35:20,354 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2023-12-19 14:32:22,566 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 0.102961 s\n" + "2023-12-19 17:35:20,355 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 0.083895 s\n" ] } ], @@ -397,10 +397,10 @@ "id": "c576ee51-e825-4970-86e8-3e5f221f145c", "metadata": { "execution": { - "iopub.execute_input": "2023-12-19T19:32:22.611025Z", - "iopub.status.busy": "2023-12-19T19:32:22.610800Z", - "iopub.status.idle": "2023-12-19T19:32:22.700246Z", - "shell.execute_reply": "2023-12-19T19:32:22.699585Z" + "iopub.execute_input": "2023-12-19T22:35:20.402708Z", + "iopub.status.busy": "2023-12-19T22:35:20.402357Z", + "iopub.status.idle": "2023-12-19T22:35:20.488044Z", + "shell.execute_reply": "2023-12-19T22:35:20.487280Z" }, "tags": [] }, @@ -1496,9 +1496,9 @@ } }, "text/html": [ - "
- + +

CyclOps 0.2.0 release

· 4 min read
Carolyn Chong
Amrit Krishnan
diff --git a/blog/archive/index.html b/blog/archive/index.html index d5dc19fad..6a174b1d5 100644 --- a/blog/archive/index.html +++ b/blog/archive/index.html @@ -5,8 +5,8 @@ Archive | CyclOps - - + +

Archive

Archive

2023​

diff --git a/blog/index.html b/blog/index.html index bdb74048d..1fe407251 100644 --- a/blog/index.html +++ b/blog/index.html @@ -5,8 +5,8 @@ Blog | CyclOps - - + +

· 4 min read
Carolyn Chong
Amrit Krishnan
diff --git a/blog/tags/0-2-0/index.html b/blog/tags/0-2-0/index.html index c2d8f1ffb..3f4d103a1 100644 --- a/blog/tags/0-2-0/index.html +++ b/blog/tags/0-2-0/index.html @@ -5,8 +5,8 @@ One post tagged with "0.2.0" | CyclOps - - + +

One post tagged with "0.2.0"

View All Tags

· 4 min read
Carolyn Chong
Amrit Krishnan
diff --git a/blog/tags/index.html b/blog/tags/index.html index 24d68f193..7007c30d4 100644 --- a/blog/tags/index.html +++ b/blog/tags/index.html @@ -5,8 +5,8 @@ Tags | CyclOps - - + +

Tags

diff --git a/docs/intro/index.html b/docs/intro/index.html index 1ae9dfb01..8119ccc4c 100644 --- a/docs/intro/index.html +++ b/docs/intro/index.html @@ -5,8 +5,8 @@ intro | CyclOps - - + +

intro

Getting Started​

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CyclOps

Cyclical development towards Operationalizing ML models for healthcare

Rigorous Evaluation

CyclOps APIs support rigorous evaluation across patient sub-populations

Monitoring

CyclOps supports monitoring of clinical ML models for performance degradation

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Markdown page example