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dc.contributorUniversitat Ramon Llull. La Salle
dc.contributor.authorPeiro, Joan Carles
dc.date.accessioned2025-07-11T08:47:23Z
dc.date.available2025-07-11T08:47:23Z
dc.date.issued2021-05-31
dc.identifier.issn1557-8593ca
dc.identifier.urihttp://hdl.handle.net/20.500.14342/5404
dc.description.abstractBackground and Aims Training a personalized control algorithm is the key component for an artificial pancreas (AP) solution. Most of documented applications of machine learning are for classification algorithms not for AP control. In this article, it is explained and proved that machine learning (ML) is a valid technology to produce an accurate regression control algorithm as lowcost solution to control a hybrid closed loop AP system.ca
dc.format.extent4 p.ca
dc.language.isoengca
dc.publisherMary Ann Liebert, Inc. Publishersca
dc.relation.ispartofThe Official Journal of ATTD Advanced Technologies & Treatments for Diabetes Conference, 2-5 juny. Virtual Diabetes Technology & Therapeutics, Vol. 23, Suplement 2: Maig 31, 2021ca
dc.rights© 2025 Sage Publications. Tots els drets reservatsca
dc.subject.otherDiabetisca
dc.subject.otherDiabetis--Tractamentca
dc.subject.otherCOVID-19 (Malaltia)ca
dc.subject.otherAprenentatge automàticca
dc.titleSARS-CoV-2 impact on diabetes type 1 patients using "hybrid closed-loop” artificial pancreasca
dc.typeinfo:eu-repo/semantics/conferenceObjectca
dc.rights.accessLevelinfo:eu-repo/semantics/openAccess
dc.embargo.termscapca
dc.subject.udc004ca
dc.subject.udc61ca
dc.subject.udc616.4ca
dc.subject.udc62ca
dc.identifier.doihttp://doi.org/10.1089/dia.2021.2525.abstractsca
dc.description.versioninfo:eu-repo/semantics/acceptedVersionca


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