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HeartSearcher: finds patients with similar arrhythmias based on heartbeat classification

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dc.contributor.authorPark, Juyoung-
dc.contributor.authorKang, Kyungtae-
dc.date.accessioned2021-06-22T18:42:27Z-
dc.date.available2021-06-22T18:42:27Z-
dc.date.issued2015-12-
dc.identifier.issn1751-8849-
dc.identifier.issn1751-8857-
dc.identifier.urihttps://scholarworks.bwise.kr/erica/handle/2021.sw.erica/16486-
dc.description.abstractLong-term electrocardiogram data can be acquired by linking a Holter monitor to a mobile phone. However, most systems of this variety are simply designed to detect arrhythmia through heartbeat classification, and do not provide any additional support for clinical decisions. HeartSearcher identifies patients with similar arrhythmias from heartbeat classifications, by summarising each patient's typical heartbeat pattern in the form of a regular expression, and then ranking patients according to the similarities of their patterns. Results obtained using electrocardiogram data from the MIT-BIH arrhythmia database show that this abstraction reduces the volume of heartbeat classifications by 98% on average, offering great potential to support clinical decisions.-
dc.format.extent6-
dc.language영어-
dc.language.isoENG-
dc.publisherINST ENGINEERING TECHNOLOGY-IET-
dc.titleHeartSearcher: finds patients with similar arrhythmias based on heartbeat classification-
dc.typeArticle-
dc.publisher.location영국-
dc.identifier.doi10.1049/iet-syb.2015.0011-
dc.identifier.scopusid2-s2.0-84948762165-
dc.identifier.wosid000365509000011-
dc.identifier.bibliographicCitationIET SYSTEMS BIOLOGY, v.9, no.6, pp 303 - 308-
dc.citation.titleIET SYSTEMS BIOLOGY-
dc.citation.volume9-
dc.citation.number6-
dc.citation.startPage303-
dc.citation.endPage308-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaCell Biology-
dc.relation.journalResearchAreaMathematical & Computational Biology-
dc.relation.journalWebOfScienceCategoryCell Biology-
dc.relation.journalWebOfScienceCategoryMathematical & Computational Biology-
dc.subject.keywordPlusECG MORPHOLOGY-
dc.subject.keywordPlusALGORITHM-
dc.subject.keywordAuthorelectrocardiography-
dc.subject.keywordAuthormedical information systems-
dc.subject.keywordAuthormedical signal detection-
dc.subject.keywordAuthormedical signal processing-
dc.subject.keywordAuthorsignal classification-
dc.subject.keywordAuthorpattern matching-
dc.subject.keywordAuthordiseases-
dc.subject.keywordAuthorpatient monitoring-
dc.subject.keywordAuthordecision making-
dc.subject.keywordAuthordata mining-
dc.subject.keywordAuthorsorting-
dc.subject.keywordAuthorabstracting-
dc.subject.keywordAuthorclinical decision support-
dc.subject.keywordAuthorheartbeat classification volume reduction-
dc.subject.keywordAuthorabstraction-
dc.subject.keywordAuthorMIT-BIH arrhythmia database-
dc.subject.keywordAuthorheartbeat pattern similarity ranking-
dc.subject.keywordAuthorpatient ranking-
dc.subject.keywordAuthorregular expression-
dc.subject.keywordAuthorpatient typical heartbeat pattern summarisation-
dc.subject.keywordAuthorsimilar arrhythmia patient identification-
dc.subject.keywordAuthorarrhythmia detection-
dc.subject.keywordAuthormobile phone-
dc.subject.keywordAuthorHolter monitor-
dc.subject.keywordAuthorlong-term electrocardiogram data acquisition-
dc.subject.keywordAuthorsimilar arrhythmia patient search-
dc.subject.keywordAuthorHeartSearcher-
dc.identifier.urlhttps://ietresearch.onlinelibrary.wiley.com/doi/10.1049/iet-syb.2015.0011-
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Kang, Kyung tae
ERICA 소프트웨어융합대학 (DEPARTMENT OF ARTIFICIAL INTELLIGENCE)
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