Predicting the physiological effects of multiple drugs using electronic health record
收藏NIAID Data Ecosystem2026-05-02 收录
下载链接：
https://zenodo.org/record/14026574
下载链接
链接失效反馈官方服务：
资源简介：
Supplementary Data 1. Optimized hyperparameters of the XGBoost classifiers for the 20 selected measurement items.
Supplementary Data 2. Information on 416 active pharmaceutical ingredients (APIs) used to develop the machine learning models for the 20 selected measurement items.
Supplementary Data 3. List of top 20 features with the highest feature importance for each XGBoost classifier according to the SHAP analysis (Fig. 4).
Supplementary Data 4. AUROC of the XGBoost classifiers for the 20 measurement items by using pairwise combinations of feature types as input, and using race-specific and sex-specific MIMIC-IV datasets.
创建时间：
2024-11-01
