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CGL

Collaborative Graph Learning with Auxiliary Text for Temporal Event Prediction in Healthcare

Requirements

Packages

  • python 3
  • numpy
  • sklearn
  • pandas
  • nltk
  • tensorflow

Prepare the environment

  1. Install all required softwares and packages.
pip install -r requirements.txt
  1. In the python console, download the stopwords and punkt corpus required by nltk.
import nltk


nltk.download('stopwords')
nltk.download('punkt')

Download the MIMIC-III dataset

Go to https://mimic.physionet.org/ for access. Once you have the authority for the dataset, download the dataset and extract the csv files to data/mimic3/raw/ in this project.

Preprocess the dataset

python run_preprocess.py

Train the model

  1. For the medical code prediction task.
python train_codes.py
  1. For the heart failure prediction task.
python train_hf.py