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dc.contributor.authorKaraolis, Minas A.en
dc.contributor.authorMoutiris, Joseph Antoniouen
dc.contributor.authorPapaconstantinou, L.en
dc.contributor.authorPattichis, Constantinos S.en
dc.creatorKaraolis, Minas A.en
dc.creatorMoutiris, Joseph Antoniouen
dc.creatorPapaconstantinou, L.en
dc.creatorPattichis, Constantinos S.en
dc.date.accessioned2019-11-13T10:40:38Z
dc.date.available2019-11-13T10:40:38Z
dc.date.issued2009
dc.identifier.isbn978-1-4244-3296-7
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/54219
dc.description.abstractAlthough significant progress has been made in the diagnosis and treatment of coronary heart disease (CHD), further investigation is still needed. The objective of this study was to develop a data mining system using association analysis based on the apriori algorithm for the assessment of heart event related risk factors. The events investigated were: myocardial infarction (MI), percutaneous coronary intervention (PCI), and coronary artery bypass graft surgery (CABG). A total of 369 cases were collected from the Paphos CHD Survey, most of them with more than one event. The most important risk factors, as extracted from the association rule analysis were: sex (male), smoking, high density lipoprotein, glucose, family history, and history of hypertension. Most of these risk factors were also extracted by our group in a previous study using the C4.5 decision tree algorithms, and by other investigators. Further investigation with larger data sets is still needed to verify these findings. ©2009 IEEE.en
dc.sourceProceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009en
dc.source31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009en
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-77950974607&doi=10.1109%2fIEMBS.2009.5334656&partnerID=40&md5=582e57d7ea2d771947263909fd27e87d
dc.subjectDiagnosisen
dc.subjectHearten
dc.subjectRisk factorsen
dc.subjectBiologyen
dc.subjectMyocardial infarctionen
dc.subjectData setsen
dc.subjectData miningen
dc.subjectGlucoseen
dc.subjectDecision treesen
dc.subjectC4.5 decision tree algorithmen
dc.subjectCoronary artery bypass graften
dc.subjectCoronary heart diseaseen
dc.subjectPercutaneous coronary interventionen
dc.subjectRelated risken
dc.subjectApriori algorithmsen
dc.subjectAssociation analysisen
dc.subjectAssociation rulesen
dc.subjectAssociative processingen
dc.subjectData mining systemen
dc.subjectHigh density lipoproteinen
dc.titleAssociation rule analysis for the assessment of the risk of coronary heart eventsen
dc.typeinfo:eu-repo/semantics/conferenceObject
dc.identifier.doi10.1109/IEMBS.2009.5334656
dc.description.startingpage6238
dc.description.endingpage6241
dc.author.faculty002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.departmentΤμήμα Πληροφορικής / Department of Computer Science
dc.type.uhtypeConference Objecten
dc.description.notes<p>Conference code: 79618en
dc.description.notesCited By :17</p>en
dc.contributor.orcidPattichis, Constantinos S. [0000-0003-1271-8151]
dc.gnosis.orcid0000-0003-1271-8151


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