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dc.contributor.author Jonsson, Anders
dc.date.accessioned 2022-10-03T07:06:29Z
dc.date.available 2022-10-03T07:06:29Z
dc.date.issued 2019
dc.identifier.citation Jonsson A. Deep reinforcement learning in medicine. Kidney Dis. 2019 Feb;5(1):18-22. DOI: 10.1159/000492670
dc.identifier.issn 2296-9381
dc.identifier.uri http://hdl.handle.net/10230/54236
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.language.iso eng
dc.publisher Karger (S. Karger AG)
dc.relation.ispartof Kidney Dis. 2019 Feb;5(1):18-22
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.uri https://creativecommons.org/licenses/by-nc/4.0/
dc.title Deep reinforcement learning in medicine
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1159/000492670
dc.subject.keyword Artificial intelligence
dc.subject.keyword Reinforcement learning
dc.subject.keyword Deep learning
dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/TIN2015-67959-P
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion

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