Early Sepsis Prediction Using Ensemble Learning With Deep Features and Artificial Features Extracted From Clinical Electronic Health Records

• Published in: Critical care medicine Vol. 48; no. 12; p. e1337
• Main Authors: He, Zhengling, Du, Lidong, Zhang, Pengfei, Zhao, Rongjian, Chen, Xianxiang, Fang, Zhen
• Format: Journal Article
• Language: English
• Published: United States 01.12.2020

Sepsis is caused by infection and subsequent overreaction of immune system and will severely threaten human life. The early prediction is important for the treatment of sepsis. This report aims to develop an early prediction method for sepsis 6 hours ahead on the basis of clinical electronic health...