Detection of heart valve diseases by using fuzzy discrete hidden Markov model

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dc.contributor.authorUguz, Harun
dc.contributor.authorArslan, Ahmet
dc.contributor.authorSaracoglu, Ridvan
dc.contributor.authorTurkoglu, Ibrahim
dc.date.accessioned2020-03-26T17:26:37Z
dc.date.available2020-03-26T17:26:37Z
dc.date.issued2008
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractIn the present study, biomedical based application was developed to classify the data belongs to normal and abnormal samples generated by Doppler ultrasound. This study consists of raw data obtaining and pre-processing, feature extraction and classification steps. In the pre-processing step, a high-pass filter, white de-noising and normalization were used. During the feature extraction step, wavelet entropy was applied by wavelet transform and short time fourier transform. Obtained features were classified by fuzzy discrete hidden Markov model (FDHMM). For this purpose, a FDHMM that consists of Sugeno and Choquet integrals and lambda fuzzy measurement was defined to eliminate statistical dependence assumptions to increase the performance and to have better flexibility. Moreover, Sugeno integral was used together with triangular norms that are mentioned frequently in the literature in order to increase the performance. Experimental results show that recognition rate obtained by Sugeno fuzzy integral with triangular norm is more successful than recognition rates obtained by standard discrete HMM (DHMM) and Choquet integral based FDHMM. In addition to this, it is shown in this study that the performance of the Sugeno integral based method is better than the performances of artificial neural network (ANN) and HMM based classification systems that were used in previous studies of the authors. (c) 2007 Elsevier Ltd. All rights reserved.en_US
dc.identifier.doi10.1016/j.eswa.2007.05.004en_US
dc.identifier.endpage2811en_US
dc.identifier.issn0957-4174en_US
dc.identifier.issn1873-6793en_US
dc.identifier.issue4en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage2799en_US
dc.identifier.urihttps://dx.doi.org/10.1016/j.eswa.2007.05.004
dc.identifier.urihttps://hdl.handle.net/20.500.12395/22303
dc.identifier.volume34en_US
dc.identifier.wosWOS:000253521900058en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherPERGAMON-ELSEVIER SCIENCE LTDen_US
dc.relation.ispartofEXPERT SYSTEMS WITH APPLICATIONSen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectpattern recognitionen_US
dc.subjectDoppler heart soundsen_US
dc.subjectwavelet decompositionen_US
dc.subjectfuzzy discrete hidden Markov modelen_US
dc.subjecttriangular normsen_US
dc.titleDetection of heart valve diseases by using fuzzy discrete hidden Markov modelen_US
dc.typeArticleen_US

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