Create counterfactual trajectory of a signal given past trajectory and some contexts (Please see the pdf file for a more detailed description of the model and the data pipeline)
- PDF file
- Detailed write up of the model and results
- Python files
- EM.py: perform inference and parameter estimation
- plot.py: plot predicted states and observations
- Notebook files
- Pipeline_Preprocessing: extract relevant data from database files; preprocess; perform inference, parameter estimation and prediction
- Pipeline_Training: given preprocessed file, perform training, can perform hyperparameter validation and training on multiple signals through parallel computing (using ipyparallel)
- DLM: simulation to evaluate model's performance
- Old dev files
- EM_individual_params: EM for learning individual parameters (incomplete)
- preprocess.py: preprocess data into format usable for EM.py (more general version is in Pipeline_Preprocessing.py)
- Population Level Analysis: assume the same set of parameters for all patients; fit to real data
- Individual Level Analysis: assume a set of parameters for each patients; fit to real data
- Source Data Analysis: some analysis on the real data set before and after preprocessing
- Playground: place to do small analysis and testing