A new approach to early diagnosis of congestive heart failure disease by using Hilbert-Huang transform

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dc.authoridALTAN, Gokhan/0000-0001-7883-3131
dc.authoridAllahverdi, Novruz/0000-0001-9807-884X
dc.contributor.authorAltan, Gokhan
dc.contributor.authorKutlu, Yakup
dc.contributor.authorAllahverdi, Novruz
dc.date.accessioned2024-09-18T20:11:47Z
dc.date.available2024-09-18T20:11:47Z
dc.date.issued2016
dc.departmentHatay Mustafa Kemal Üniversitesien_US
dc.description.abstractCongestive heart failure (CHF) is a degree of cardiac disease occurring as a result of the heart's inability to pump enough blood for the human body. In recent studies, coronary artery disease (CAD) is accepted as the most important cause of CHF. This study focuses on the diagnosis of both the CHF and the CAD. The Hilbert-Huang transform (HHT), which is effective on nonlinear and non-stationary signals, is used to extract the features from R-R intervals obtained from the raw electrocardiogram data. The statistical features are extracted from instinct mode functions that are obtained applying the HHT to R-R intervals. Classification performance is examined with extracted statistical features using a multilayer perceptron neural network. The designed model classified the CHF, the CAD patients and a normal control group with rates of 97.83%, 93.79% and 100%, accuracy, specificity and sensitivity, respectively. Also, early diagnosis of the CHF was performed by interpretation of the CAD with a classification accuracy rate of 97.53%, specificity of 98.18% and sensitivity of 97.13%. As a result, a single system having the ability of both diagnosis and early diagnosis of CHF is performed by integrating the CAD diagnosis method to the CHF diagnosis method. (C) 2016 Elsevier Ireland Ltd. All rights reserved.en_US
dc.identifier.doi10.1016/j.cmpb.2016.09.003
dc.identifier.endpage34en_US
dc.identifier.issn0169-2607
dc.identifier.issn1872-7565
dc.identifier.pmid28110727en_US
dc.identifier.scopus2-s2.0-84988402613en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage23en_US
dc.identifier.urihttps://doi.org/10.1016/j.cmpb.2016.09.003
dc.identifier.urihttps://hdl.handle.net/20.500.12483/9070
dc.identifier.volume137en_US
dc.identifier.wosWOS:000386750300004en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherElsevier Ireland Ltden_US
dc.relation.ispartofComputer Methods and Programs in Biomedicineen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCongestive heart failureen_US
dc.subjectCoronary artery diseaseen_US
dc.subjectHilbert-Huang transformen_US
dc.subjectECGen_US
dc.subjectMultilayer perceptronen_US
dc.subjectHRVen_US
dc.titleA new approach to early diagnosis of congestive heart failure disease by using Hilbert-Huang transformen_US
dc.typeArticleen_US

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