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Code for TKDE paper: Patient Health Representation Learning via Correlational Sparse Prior of Medical Features.

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# SAFARI

This is the code for the paper: _Patient Health Representation Learning via Correlational Sparse Prior of Medical Features_, published in TKDE (IEEE Transactions on Knowledge and Data Engineering, currently Early Access).

Paper Link🔗: https://ieeexplore.ieee.org/document/9992086/

Currently, we provide the code of experiments on the MIMIC-III dataset for reference.
However, due to the copyright policies of the MIMIC-III dataset, we only present the code without source data here.

- The main code is in the jupyter notebook: SAFARI_submission_MIMIC.ipynb.
- The directory './utils/' contains the codes for data preprocessing and performance metrics.
- The directory './model/' saves the trained model checkpoint.

If our work helps, please don't forget to cite our paper☺️
Bibtex is provided below:

```
@article{ma2022patient,
  title={Patient Health Representation Learning via Correlational Sparse Prior of Medical Features},
  author={Ma, Xinyu and Wang, Yasha and Chu, Xu and Ma, Liantao and Tang, Wen and Zhao, Junfeng and Yuan, Ye and Wang, Guoren},
  journal={IEEE Transactions on Knowledge and Data Engineering},
  year={2022},
  publisher={IEEE}
}
```

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