作者
Tyler J Loftus, Amanda C Filiberto, Yanjun Li, Jeremy Balch, Allyson C Cook, Patrick J Tighe, Philip A Efron, Gilbert R Upchurch Jr, Parisa Rashidi, Xiaolin Li, Azra Bihorac
发表日期
2020/8/1
期刊
Surgery
卷号
168
期号
2
页码范围
253-266
出版商
Mosby
简介
Background
Surgical patients incur preventable harm from cognitive and judgment errors made under time constraints and uncertainty regarding patients’ diagnoses and predicted response to treatment. Decision analysis and techniques of reinforcement learning theoretically can mitigate these challenges but are poorly understood and rarely used clinically. This review seeks to promote an understanding of decision analysis and reinforcement learning by describing their use in the context of surgical decision-making.
Methods
Cochrane, EMBASE, and PubMed databases were searched from their inception to June 2019. Included were 41 articles about cognitive and diagnostic errors, decision-making, decision analysis, and machine-learning. The articles were assimilated into relevant categories according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews …
引用总数
20202021202220232024141064
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