Decision analysis and reinforcement learning in surgical decision-making.

ABSTRACT:

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 categ

SUBMITTER: Loftus TJ 

PROVIDER: S-EPMC7390703 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature