Using a machine learning approach to predict mortality in critically ill influenza patients: a cross-sectional retrospective multicentre study in Taiwan.

Chien-An HuChia-Ming ChenYen-Chun FangShinn-Jye LiangHao-Chien WangWen-Feng FangChau-Chyun SheuWann-Cherng PerngKuang-Yao YangKuo-Chin KaoChieh-Liang WuChwei-Shyong TsaiMing-Yen LinWen-Cheng Chaonull null

Published in: BMJ open (2020)

We used a real-world data set and applied an ML approach, mainly XGBoost, to establish a practical and explainable mortality prediction model in critically ill influenza patients.

Keyphrases

end stage renal disease
machine learning
chronic kidney disease
newly diagnosed
cardiovascular events
risk factors
cardiovascular disease
patient reported outcomes
cross sectional
big data