Machine Learning-Based Prediction of Acute Kidney Injury Following Pediatric Cardiac Surgery: Model Development and Validation Study.
Xiao-Qin LuoYi-Xin KangShao-Bin DuanPing YanGuo-Bao SongNing-Ya ZhangShi-Kun YangJing-Xin LiHui ZhangPublished in: Journal of medical Internet research (2023)
The interpretable XGBoost models provide practical tools for the early prediction of CSA-AKI, which are valuable for risk stratification and perioperative management of pediatric patients undergoing cardiac surgery.