Medical Concept Embedding with Multiple Ontological Representations (IJCAI-19)

This repo contains the PyTorch implementation of the paper Medical Concept Embedding with Multiple Ontological Representations in IJCAI-19. [paper] [dataset]

Requirements

The codes have been tested with the following packages:

• Python 3.5
• PyTorch 0.4.1

Quick Demo

To run the model, clone the repo and decompress the demo data archive by executing the following commands:

git clone [email protected]:cscihkbu/mmore.git
cd mmore
python mmore_dxrx.py

Or you can train the model with diagnoses only by:

python mmore_dx.py

Data Format and Organization

We follow the same input data organization used by GRAM. Please refer to the section STEP 4: How to prepare your own dataset of the GRAM repository for more details.

Citation

If you find the paper or the implementation helpful, please cite the following paper:

@inproceedings{song2019learning,
  title={Medical concept embedding with multiple ontological representations},
  author={Song, Lihong and Cheong, Chin Wang and Yin, Kejing and Cheung, William K. and Fung, Benjamin C. M. and Poon, Jonathan},
  booktitle={Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence ({IJCAI-19})},
  pages={4613--4619},
  year={2019},
  organization={AAAI Press}
}