A cloud-based platform for the non-invasive management of coronary artery disease

dc.contributor.authorSakellarios, Antonis
dc.contributor.authorCorreia J.
dc.contributor.authorKyriakidis S.
dc.contributor.authorGeorga E.
dc.contributor.authorTachos N.
dc.contributor.authorSiogkas, Panagiotis
dc.contributor.authorSans F.
dc.contributor.authorStofella P.
dc.contributor.authorMassimiliano V.
dc.contributor.authorClemente, Alberto
dc.contributor.authorRocchiccioli S.
dc.contributor.authorPelosi, Gualtiero
dc.contributor.authorFilipovic, Nenad
dc.contributor.authorFotiadis D.
dc.date.accessioned2021-04-20T21:34:44Z
dc.date.available2021-04-20T21:34:44Z
dc.date.issued2020
dc.description.abstract© 2020 Informa UK Limited, trading as Taylor & Francis Group. We present the architecture and the usability testing of a novel cloud-based platform, which integrates cyber-physical systems and interoperability standards enabling a clinical decision support system for risk stratification, diagnosis, prognosis and treatment of CAD. In this work multi-disciplinary human data were used for the development of machine learning and computational biomechanics based predictive models. Two Lab-on-Chip devices have been integrated into the cloud platform. A targeted RNA-panel provides the mRNA gene expression values for the stratification algorithm. The results of the usability testing demonstrate that the platform is efficient, accurate and performs all developed tasks quickly.
dc.identifier.doi10.1080/17517575.2020.1746975
dc.identifier.issn1751-7575
dc.identifier.scopus2-s2.0-85083557430
dc.identifier.urihttps://scidar.kg.ac.rs/handle/123456789/12729
dc.rightsrestrictedAccess
dc.sourceEnterprise Information Systems
dc.titleA cloud-based platform for the non-invasive management of coronary artery disease
dc.typearticle

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