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dc.contributor.authorLopez Martinez, Daniel
dc.contributor.authorPicard, Rosalind W.
dc.date.accessioned2021-11-23T17:28:18Z
dc.date.available2021-11-02T11:47:03Z
dc.date.available2021-11-23T17:28:18Z
dc.date.issued2019-07
dc.identifier.isbn9781538613122
dc.identifier.isbn9781538613115
dc.identifier.urihttps://hdl.handle.net/1721.1/137059.2
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.isversionof10.1109/EMBC.2019.8857295en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcearXiven_US
dc.titleDeep Reinforcement Learning for Optimal Critical Care Pain Management with Morphine using Dueling Double-Deep Q Networksen_US
dc.typeArticleen_US
dc.identifier.citationLopez-Martinez, Daniel, Eschenfeldt, Patrick, Ostvar, Sassan, Ingram, Myles, Hur, Chin et al. 2019. "Deep Reinforcement Learning for Optimal Critical Care Pain Management with Morphine using Dueling Double-Deep Q Networks." 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).en_US
dc.contributor.departmentMassachusetts Institute of Technology. Institute for Medical Engineering & Scienceen_US
dc.contributor.departmentProgram in Media Arts and Sciences (Massachusetts Institute of Technology)en_US
dc.relation.journal2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)en_US
dc.eprint.versionOriginal manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2021-07-06T14:06:27Z
dspace.orderedauthorsLopez-Martinez, D; Eschenfeldt, P; Ostvar, S; Ingram, M; Hur, C; Picard, Ren_US
dspace.date.submission2021-07-06T14:06:29Z
mit.licenseOPEN_ACCESS_POLICY
mit.metadata.statusPublication Information Neededen_US


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