Ве молиме користете го овој идентификатор да го цитирате или поврзете овој запис: http://hdl.handle.net/20.500.12188/8873
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dc.contributor.authorSimjanoska, Monikaen_US
dc.contributor.authorGjoreski, Martinen_US
dc.contributor.authorMadevska Bogdanova, Anaen_US
dc.contributor.authorKoteska, Bojanaen_US
dc.contributor.authorGams, Matjažen_US
dc.contributor.authorTasič, Jurijen_US
dc.date.accessioned2020-09-04T13:56:38Z-
dc.date.available2020-09-04T13:56:38Z-
dc.date.issued2018-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/8873-
dc.publisherSCITEPRESS - Science and Technology Publicationsen_US
dc.titleECG-derived Blood Pressure Classification using Complexity Analysis-based Machine Learningen_US
dc.relation.conferenceProceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologiesen_US
dc.identifier.doi10.5220/0006538202820292-
item.grantfulltextnone-
item.fulltextNo Fulltext-
crisitem.author.deptFaculty of Computer Science and Engineering-
crisitem.author.deptFaculty of Computer Science and Engineering-
crisitem.author.deptFaculty of Computer Science and Engineering-
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers
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