Reinforcement Learning for Clinical Decision Support in Critical Care: Comprehensive Review.

ABSTRACT:

Background

Decision support systems based on reinforcement learning (RL) have been implemented to facilitate the delivery of personalized care. This paper aimed to provide a comprehensive review of RL applications in the critical care setting.

Objective

This review aimed to survey the literature on RL applications for clinical decision support in critical care and to provide insight into the challenges of applying various RL models.

Methods

We performed an extensive search of the following databases: PubMed, Google Scholar, Institute of Electrical and Electronics Engineers (IEEE), ScienceDirect, Web of Science, Medical Literature Analysis and Retrieval System Online (MEDLINE), and Excerpta Medica Database (EMBASE). Studies published over the past 10 years (2010-2019)

SUBMITTER: Liu S 

PROVIDER: S-EPMC7400046 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature