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Unsupervised detection and classification of heartbeats using the dissimilarity matrix in pcg signals

dc.contributor.authorTorre Cruz, J.
dc.contributor.authorMartínez Muñoz, D.
dc.contributor.authorRuiz Reyes, N.
dc.contributor.authorMuñoz Montoro, Antonio Jesús 
dc.contributor.authorPuentes Chiachio, M.
dc.contributor.authorCanadas Quesada, F. J.
dc.date.accessioned2023-02-01T11:51:49Z
dc.date.available2023-02-01T11:51:49Z
dc.date.issued2022
dc.identifier.citationComputer Methods and Programs in Biomedicine, 221 (2022); doi:10.1016/j.cmpb.2022.106909
dc.identifier.issn0169-2607
dc.identifier.urihttp://hdl.handle.net/10651/66149
dc.description.sponsorshipThis work was supported by the Programa Operativo FEDER Andalucía 2014–2020 under project with reference 1257914, the Ministry of Economy, Knowledge and University, Junta de Andalucia under Project P18-RT-1994 and the Spanish Ministry of Science and Innovation under Project PID2020-119082RB-C21.
dc.language.isoeng
dc.relation.ispartofComputer Methods and Programs in Biomedicine
dc.rights© 2022 Elsevier B.V.
dc.sourceScopus
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85131120467&doi=10.1016%2fj.cmpb.2022.106909&partnerID=40&md5=2b327e2bcfb5b723e967195299f90b82
dc.titleUnsupervised detection and classification of heartbeats using the dissimilarity matrix in pcg signals
dc.typejournal article
dc.identifier.doi10.1016/j.cmpb.2022.106909
dc.relation.projectIDMCIN/PID2020-119082RB-C21
dc.relation.publisherversionhttp://dx.doi.org/10.1016/j.cmpb.2022.106909


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