Predicting the hyper-local prevalence of chronic kidney disease with stochastic gradient boosting
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Updated
Apr 2, 2019 - Jupyter Notebook
Predicting the hyper-local prevalence of chronic kidney disease with stochastic gradient boosting
Evaluating racial and/or ethnic disparities in the timeliness of nephrology care amongst patients with newly diagnosed CKD. This work will look at time to nephrology follow up once patients are diagnosed with CKD Stage 3 and CKD Stage 4.
Statistical code to replicate the analyses in "The Presence and Impact of Multimorbidity Clusters on Adverse Outcome Across the Spectrum of Kidney Function".
Containerized workflow for analysis of human diabetic kidney disease by snRNA-seq and snATAC-seq
Towards a CKD (Chronic Kidney Disease) dataset.
Chronic kidney disease (CKD) is a long-term disorder which causes the kidneys to not function as well as they should.Our goal is to predict whether a subject has the chance of getting chronic kidney disease from a given set of data using machine learning.
Containerized workflow for single cell detection of loss of Y chromosome and other mosaic chromosomal alterations in chronic kidney disease
A Python library for kidney failure risk estimation using Tangri's KFRE model
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