Optimal sepsis patient treatment using human-in-the-loop artificial intelligence
作者：
Highlights：
• Formulates a generalized optimization model to prescribe the optimal treatment.
• Determines the optimal quantity of fluids resuscitation to septic patients.
• Investigates the resilience of the proposed model in the absence of human experts.
• Proposes a feature selection procedure for inverse classifiers.
• Augments the theoretical literature on inverse classifiers.
摘要
•Formulates a generalized optimization model to prescribe the optimal treatment.•Determines the optimal quantity of fluids resuscitation to septic patients.•Investigates the resilience of the proposed model in the absence of human experts.•Proposes a feature selection procedure for inverse classifiers.•Augments the theoretical literature on inverse classifiers.
论文关键词：Sepsis,Fluid resuscitation,Artificial intelligence,Optimization,Inverse classifier
论文评审过程：Received 18 September 2020, Revised 17 November 2020, Accepted 6 December 2020, Available online 17 December 2020, Version of Record 9 January 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2020.114476
