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Exploratory outlier detection for acceleromyographic neuromuscular monitoring : Machine learning approach

dc.contributor.authorVerdonck, Michaël
dc.contributor.authorCarvalho, Hugo
dc.contributor.authorBerghmans, Johan
dc.contributor.authorForget, Patrice
dc.contributor.authorPoelaert, Jan
dc.date.accessioned2023-02-20T12:09:01Z
dc.date.available2023-02-20T12:09:01Z
dc.date.issued2021-06-21
dc.identifier.citationVerdonck , M , Carvalho , H , Berghmans , J , Forget , P & Poelaert , J 2021 , ' Exploratory outlier detection for acceleromyographic neuromuscular monitoring : Machine learning approach ' , Journal of Medical Internet Research , vol. 23 , no. 6 , e25913 . https://doi.org/10.2196/25913en
dc.identifier.issn1439-4456
dc.identifier.otherPURE: 220994091
dc.identifier.otherPURE UUID: aee4307e-67a7-4274-9859-1dfbd3728b25
dc.identifier.otherScopus: 85108676697
dc.identifier.otherPubMed: 34152273
dc.identifier.otherORCID: /0000-0001-5772-8439/work/129409689
dc.identifier.urihttps://hdl.handle.net/2164/20111
dc.descriptionFunding Information: This research was funded by the Flanders Innovation and Entrepreneurship Fund, the Willy Gepts Fund for Scientific Research, and the Society for Anesthesia and Resuscitation of Belgium (SARB). Publisher Copyright: © Michaël Verdonck, Hugo Carvalho, Johan Berghmans, Patrice Forget, Jan Poelaert. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 06.06.2021. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.en
dc.language.isoeng
dc.relation.ispartofJournal of Medical Internet Researchen
dc.rightsThis is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.en
dc.subjectSDG 3 - Good Health and Well-beingen
dc.subjectAcceleromyographyen
dc.subjectAnesthesiologyen
dc.subjectMachine learningen
dc.subjectMonitoring devicesen
dc.subjectMonitorsen
dc.subjectNeuromuscularen
dc.subjectNeuromuscular monitoringen
dc.subjectOutlier analysisen
dc.subjectPostoperative residual curarizationen
dc.subjectTrain-of-fouren
dc.subjectRA0421 Public health. Hygiene. Preventive Medicineen
dc.subjectHealth Informaticsen
dc.subjectSupplementary Dataen
dc.subject.lccRA0421en
dc.titleExploratory outlier detection for acceleromyographic neuromuscular monitoring : Machine learning approachen
dc.typeJournal articleen
dc.contributor.institutionUniversity of Aberdeen.Other Applied Health Sciencesen
dc.description.statusPeer revieweden
dc.description.versionPublisher PDFen
dc.identifier.doihttps://doi.org/10.2196/25913
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85108676697&partnerID=8YFLogxKen
dc.identifier.vol23en
dc.identifier.iss6en


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