A cloud-based platform for the non-invasive management of coronary artery disease
dc.contributor.author | Sakellarios, Antonis | |
dc.contributor.author | Correia J. | |
dc.contributor.author | Kyriakidis S. | |
dc.contributor.author | Georga E. | |
dc.contributor.author | Tachos N. | |
dc.contributor.author | Siogkas, Panagiotis | |
dc.contributor.author | Sans F. | |
dc.contributor.author | Stofella P. | |
dc.contributor.author | Massimiliano V. | |
dc.contributor.author | Clemente, Alberto | |
dc.contributor.author | Rocchiccioli S. | |
dc.contributor.author | Pelosi, Gualtiero | |
dc.contributor.author | Filipovic, Nenad | |
dc.contributor.author | Fotiadis D. | |
dc.date.accessioned | 2021-04-20T21:34:44Z | |
dc.date.available | 2021-04-20T21:34:44Z | |
dc.date.issued | 2020 | |
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.doi | 10.1080/17517575.2020.1746975 | |
dc.identifier.issn | 1751-7575 | |
dc.identifier.scopus | 2-s2.0-85083557430 | |
dc.identifier.uri | https://scidar.kg.ac.rs/handle/123456789/12729 | |
dc.rights | restrictedAccess | |
dc.source | Enterprise Information Systems | |
dc.title | A cloud-based platform for the non-invasive management of coronary artery disease | |
dc.type | article |
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