This codebase contains python implementation of the paper:
Validation and refinement of two interpretable models for COVID-19 prognosis prediction @author:Kai Chang#, Ting Jia#, Yana Zhou#, Zixin Shu#, Chaoan Peng, Xugui Li, Qiguang Zheng, Haoyu Tian, Jianan Xia, Kuo Yang, Ning Wang, Jifen Liu, Jing Sun, Hailong Sun, Xinyan Wang, Jinghui Ji, Dengying Yan, Qunsheng Zou, Taane G. Clark, Baoyan Liu*, Xiaodong Li*, Yonghong Peng*, Xuezhong Zhou*
To run the model, execute the following command:
First run the preprocess.py file to preprocess the data, and generate training and testing files.
Then run the main.py file to train and test the prediction model.
The codebase is implemented in Python 3.6.5. Required packages are:
numpy
xgboost
pandas
sklearn
matplotlib
lifelines
If you found this codebase useful, please cite:
title={Validation and refinement of two interpretable models for COVID-19 prognosis prediction},
author={Kai Chang#, Ting Jia#, Yana Zhou#, Zixin Shu#, Chaoan Peng, Xugui Li, Qiguang Zheng, Haoyu Tian, Jianan Xia, Kuo Yang, Ning Wang, Jifen Liu, Jing Sun, Hailong Sun, Xinyan Wang, Jinghui Ji, Dengying Yan, Qunsheng Zou, Taane G. Clark, Baoyan Liu*, Xiaodong Li*, Yonghong Peng*, Xuezhong Zhou*},
year={2020}