Reinforcement learning for intelligent healthcare applications: A survey

作者:

Highlights:

• Survey of the applications of Reinforcement Learning (RL) in healthcare domains.

• Identification of seven categories with respect to the most relevant field of applications of RL approaches in medicine.

• A brief discussion to highlight some considerations that can be taken in account when new prediction models get defined in the field of precision medicine.

• Analysis of the distribution of the surveyed solutions with respect to their category, adopted Reinforcement Learning approaches, their impact in terms of citations, and publication year.

• Group the healthcare domains in seven classes of application and for each one stating an overview of the application of Reinforcement-Learning-based approach.

摘要

•Survey of the applications of Reinforcement Learning (RL) in healthcare domains.•Identification of seven categories with respect to the most relevant field of applications of RL approaches in medicine.•A brief discussion to highlight some considerations that can be taken in account when new prediction models get defined in the field of precision medicine.•Analysis of the distribution of the surveyed solutions with respect to their category, adopted Reinforcement Learning approaches, their impact in terms of citations, and publication year.•Group the healthcare domains in seven classes of application and for each one stating an overview of the application of Reinforcement-Learning-based approach.

论文关键词:Artificial intelligence,Reinforcement learning,Healthcare,Personalized medicine

论文评审过程:Received 11 December 2019, Revised 1 September 2020, Accepted 22 September 2020, Available online 28 September 2020, Version of Record 5 October 2020.

论文官网地址:https://doi.org/10.1016/j.artmed.2020.101964