Comparison of Principal Component Analysis and Radial Basis Function Network for Diagnosis of Hypertension

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dc.contributor.authorTurk, Fuat
dc.contributor.authorBarisci, Necaattin
dc.contributor.authorCiftci, Aydin
dc.contributor.authorEkmekci, Yakup
dc.date.accessioned2020-06-25T18:06:53Z
dc.date.available2020-06-25T18:06:53Z
dc.date.issued2012
dc.departmentKırıkkale Üniversitesi
dc.description9th International Conference on Electronics Computer and Computation (ICECCO 2012) -- NOV 01-03, 2012 -- Ankara, TURKEY
dc.description.abstractIn this study, from 150 individuals over the age of 30 taken no drugs, sex, age, height, weight, HDL, LDL, Triglyceride, smoking and uric acid were measured. 65 of them are normal but 85 consist of the patients. Data obtained of each patient was applied Artificial Neural Network (ANN) models. The results obtained will be classified as either normal or the patient. Using Principal Component Analysis (PCA), 89% of patient individuals and 88% of normal individuals were classified correctly. Using Radial Basis Function Networks (RBFN), 89% of the patient individuals and 84% of normal individuals were classified correctly.en_US
dc.description.sponsorshipInt Assoc Univ, Surat Technol, Yildirim Elect, BMD Solaren_US
dc.identifier.citationclosedAccessen_US
dc.identifier.endpage36en_US
dc.identifier.isbn978-605-87394-6-8
dc.identifier.startpage33en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12587/5393
dc.identifier.wosWOS:000396806300009
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.language.isoen
dc.publisherTurgut Ozal Univen_US
dc.relation.ispartofIcecco'12: 9Th International Conference On Electronics, Computer And Computation
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectPrincipal Component Analysisen_US
dc.subjectPCAen_US
dc.subjectRadial Basis Function Networksen_US
dc.subjectRBFNen_US
dc.subjectHypertensionen_US
dc.titleComparison of Principal Component Analysis and Radial Basis Function Network for Diagnosis of Hypertensionen_US
dc.typeConference Object

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