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dc.contributor.advisorGodtliebsen, Fred
dc.contributor.advisorMyhre, Jonas N.
dc.contributor.authorHjerde, Sigurd Thorvald Nordtveit
dc.date.accessioned2020-05-07T07:41:41Z
dc.date.available2020-05-07T07:41:41Z
dc.date.issued2020-02-13
dc.description.abstractPatients with type 1 diabetes (T1D) must continually decide how much insulin to inject before each meal to maintain an acceptable level of blood glucose. Recent research has worked on a solution for this burden: the artificial pancreas (AP), which is a closed-loop system combining a continuous glucose monitor (CGM) and an insulin pump with a decision-making algorithm. The goal of this thesis is to implement and evaluate several hybrid closed-loop deep Q-learning (DQL) algorithms for the task of regulating blood glucose in T1D patients. Firstly, we will review the diabetes disease, its burdens and challenges, and existing treatment models. Secondly, we will study the foundations of reinforcement learning (RL) and deep reinforcement learning (DRL), with the emphasis on DQL techniques. Then we will merge the theories and implement DQL algorithms with the application of regulating blood glucose for T1D in-silico patients. Finally, we will test these algorithms on a T1D glucoregulatory simulator.en_US
dc.identifier.urihttps://hdl.handle.net/10037/18236
dc.language.isoengen_US
dc.publisherUiT Norges arktiske universiteten_US
dc.publisherUiT The Arctic University of Norwayen_US
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2020 The Author(s)
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/4.0en_US
dc.rightsAttribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)en_US
dc.subject.courseIDFYS-3900
dc.subjectReinforcement learningen_US
dc.subjectType 1 Diabetesen_US
dc.subjectArtificial pancreasen_US
dc.subjectClosed-loop controlen_US
dc.subjectContinuous glucose monitoringen_US
dc.subjectVDP::Mathematics and natural science: 400::Physics: 430en_US
dc.subjectVDP::Matematikk og Naturvitenskap: 400::Fysikk: 430en_US
dc.titleEvaluating Deep Q-Learning Techniques for Controlling Type 1 Diabetesen_US
dc.typeMaster thesisen_US
dc.typeMastergradsoppgaveen_US


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Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)