Deep reinforcement learning in medicine
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- dc.contributor.author Jonsson, Anders, 1973-
- dc.date.accessioned 2022-10-03T07:06:29Z
- dc.date.available 2022-10-03T07:06:29Z
- dc.date.issued 2019
- dc.description.abstract Reinforcement learning has achieved tremendous success in recent years, notably in complex games such as Atari, Go, and chess. In large part, this success has been made possible by powerful function approximation methods in the form of deep neural networks. The objective of this paper is to introduce the basic concepts of reinforcement learning, explain how reinforcement learning can be effectively combined with deep learning, and explore how deep reinforcement learning could be useful in a medical context.
- dc.description.sponsorship This work is partially funded by the grant TIN2015-67959 of the Spanish Ministry of Science.
- dc.format.mimetype application/pdf
- dc.identifier.citation Jonsson A. Deep reinforcement learning in medicine. Kidney Dis. 2019 Feb;5(1):18-22. DOI: 10.1159/000492670
- dc.identifier.doi http://dx.doi.org/10.1159/000492670
- dc.identifier.issn 2296-9381
- dc.identifier.uri http://hdl.handle.net/10230/54236
- dc.language.iso eng
- dc.publisher Karger (S. Karger AG)
- dc.relation.ispartof Kidney Dis. 2019 Feb;5(1):18-22
- dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/TIN2015-67959-P
- dc.rights Articles published in Kidney Diseases are licensed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license. The Version of Record of this article is available at http://www.karger.com/?doi=10.1159/000492670
- dc.rights.accessRights info:eu-repo/semantics/openAccess
- dc.rights.uri https://creativecommons.org/licenses/by-nc/4.0/
- dc.subject.keyword Artificial intelligence
- dc.subject.keyword Reinforcement learning
- dc.subject.keyword Deep learning
- dc.title Deep reinforcement learning in medicine
- dc.type info:eu-repo/semantics/article
- dc.type.version info:eu-repo/semantics/publishedVersion