zhaoli2017 / lung_brain_meta_prediction

This repo contains the code and trained model.

We describe how the structured EHR data was processed for machine learning model development using the scripts in this repository:

patient2dict --> more_feature_extraction --> pretraining-labeling --> case_control_matching --> convert4training --> dataset_setup

• Step 1: patient2dict extract useful columns from each file, and convert it into directionary format.

• Step 2: more_feature_extraction extract lab test and clinical events and save it

• Step 3: pretraining-labeling Detect the datetime of lung cancer, BM, BM_facts, hospice and expired encounter;

• Step 4: case_control_matching

• Step 5: convert4training Extract information to be sent for training, and convert the format; Add more features, like clinical events and lab test;

• Step 6: dataset_setup_retain Further clean the data, and make input for RETAIN model;

RETAIN model is forked from [https://github.com/mp2893/retain]