This is the code accompanying the Modular Clinical Decision Support Networks (MoDN) Updatable, Interpretable, and Portable Predictions for Evolving Clinical Environments abstract.
The experiments were run on python version 3.8.10. The data folder must contain the data (link to anonymized data https://zenodo.org/record/400380#.Yug5kuzP00Q) and the models folder contains the scripts used to run the different experiments and produce the plots.
The script main.py calls the preprocessing pipeline on the data, saves the preprocessed data (qst_obj) and trains the model either performing 5 times 2-fold CV (saving the different metrics) or just training a single model.
The script iio_training.py performs the IIO experiments (i.e. compartmentalization and fine tuning). The different models and performance scores are saved to the updated_centralized folder.
After having run both these files, one can run statistical_tests.py to produce the plots (uses saved metrics by the two previous scripts).
Metrics and performance scores are saved to the saved_objects folder and plots to the saved_plots folder.
baselines.py contains the functions to compute the KNN and logistic regression baselines.
dataset_generation.py puts the data in shape to be used by the models.
distributed_training_parameters.py contains the parameters used by the distributed_training.py file.
graph_functions.py contains many functions to produce some plots.
modules.py contains the module and state definitions.
training_procedures_epoct.py contains the training and testing processes for the model.
utils_distributed.py contains some utlitary functions for the compartmentalisation and fine-tuning experiments.
utils_epoct.py contins utilitary functions specific to the epoct data and utils.py general utilitary functions.
To reproduce the results reported in Modular Clinical Decision Support Networks (MoDN) Updatable, Interpretable, and Portable Predictions for Evolving Clinical Environments, install the necessary dependencies using:
sudo apt install texlive texlive-latex-extra texlive-fonts-recommended dvipng cm-super
pip install -r requirements.txt (from the root directory)
Then run the different scripts as described in the Plots paragraph.