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dc.contributor.authorHose, David Rodney
dc.contributor.authorLawford, Patricia V.
dc.contributor.authorHuberts, Wouter
dc.contributor.authorHellevik, Leif Rune
dc.contributor.authorOmholt, Stig William
dc.contributor.authorvan de Vosse, Frans
dc.date.accessioned2020-08-24T08:41:35Z
dc.date.available2020-08-24T08:41:35Z
dc.date.created2019-10-10T16:19:03Z
dc.date.issued2019
dc.identifier.citationMedical Engineering and Physics. 2019, 72 38-48.en_US
dc.identifier.issn1350-4533
dc.identifier.urihttps://hdl.handle.net/11250/2673528
dc.description.abstractThe aim of this position paper is to provide a brief overview of the current status of cardiovascular modelling and of the processes required and some of the challenges to be addressed to see wider exploitation in both personal health management and clinical practice. In most branches of engineering the concept of the digital twin, informed by extensive and continuous monitoring and coupled with robust data assimilation and simulation techniques, is gaining traction: the Gartner Group listed it as one of the top ten digital trends in 2018. The cardiovascular modelling community is starting to develop a much more systematic approach to the combination of physics, mathematics, control theory, artificial intelligence, machine learning, computer science and advanced engineering methodology, as well as working more closely with the clinical community to better understand and exploit physiological measurements, and indeed to develop jointly better measurement protocols informed by model-based understanding. Developments in physiological modelling, model personalisation, model outcome uncertainty, and the role of models in clinical decision support are addressed and ‘where-next’ steps and challenges discussed.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.titleCardiovascular models for personalised medicine: Where now and where next?en_US
dc.typeJournal articleen_US
dc.description.versionsubmittedVersionen_US
dc.source.pagenumber38-48en_US
dc.source.volume72en_US
dc.source.journalMedical Engineering and Physicsen_US
dc.identifier.doi10.1016/j.medengphy.2019.08.007
dc.identifier.cristin1736157
dc.description.localcode© 2019. This is the authors' manuscript to the article.en_US
cristin.unitcode194,65,25,0
cristin.unitcode194,64,45,0
cristin.unitnameInstitutt for sirkulasjon og bildediagnostikk
cristin.unitnameInstitutt for konstruksjonsteknikk
cristin.ispublishedtrue
cristin.fulltextpreprint
cristin.qualitycode1


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