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Graph-Text Multi-Modal Pre-training for Medical Representation Learning

This is a official PyTorch implementation of the MedGTX in "Graph-Text Multi-Modal Pre-training for Medical Representation Learning" (Sungjin Park, Seongsu Bae, Jiho Kim, Tackeun Kim, Edward Choi, CHIL 2022) PAPER

Experimental Environments

We distribute the experimental enviroments via Docker

docker pull sjpark9503/dev_env:chil2022_medgtx_env

Usage

  • Code for MIMIC-III pre-processing in preprocessing
  • Code for running experiments in gtx/run_DxPx.py and gtx/run_Rx.py
    • Please log in to W&B for logging results.
  • Pre-trained models in gtx/pretrained_models/Pre/

Citations

@inproceedings{park2022medgtx, 
  title={Graph-Text Multi-Modal Pre-training for Medical Representation Learning},
  author={Park, Sungjin and Bae, Seongsu and Kim, Jiho and Kim, Tackeun and Choi, Edward},
  booktitle={The Conference on Health, Inference, and Learning},
  year={2022}
}

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