Usage of a novel, similarity-based weighting method to diagnose atherosclerosis from carotid artery Doppler signals

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dc.contributor.authorPolat, Kemal
dc.contributor.authorLatifoglu, Fatma
dc.contributor.authorKara, Sadik
dc.contributor.authorGuenes, Salih
dc.date.accessioned2020-03-26T17:28:23Z
dc.date.available2020-03-26T17:28:23Z
dc.date.issued2008
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractIn this paper, we have proposed a novel similarity-based weighting method (SBWM), which combines similarity measure and weighting based on trend association (WBTA) method proposed by Sun Yi et al. (ICNN&B international conference, vol 1, pp 266-269, 2005). The aim of this study is to improve the classification accuracy of atherosclerosis, which is a common disease among the public. The proposed method consists of three parts: (1) feature extraction part related with atherosclerosis disease using fast Fourier transformation (FFT) modeling and calculation of maximum frequency envelope of sonograms, (2) data pre-processing part using SBWM, including different similarity measures such as cosine amplitude method, max-min method, absolute exponential method, and exponential similarity coefficient, and (3) classification part using artificial immune recognition system (AIRS) and Fuzzy-AIRS classifier algorithms. While AIRS and Fuzzy-AIRS algorithms obtained 71.92 and 78.94% success rates, respectively, the combination of SBWM with classifier algorithms including AIRS and Fuzzy-AIRS obtained 100% success rate on all the similarity measures. These results show that SBWM has produced very promising results in the classification of atherosclerosis from carotid artery Doppler signals. In future, we will use a larger dataset to test the proposed method.en_US
dc.identifier.doi10.1007/s11517-007-0279-6en_US
dc.identifier.endpage362en_US
dc.identifier.issn0140-0118en_US
dc.identifier.issn1741-0444en_US
dc.identifier.issue4en_US
dc.identifier.pmid17960442en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage353en_US
dc.identifier.urihttps://dx.doi.org/10.1007/s11517-007-0279-6
dc.identifier.urihttps://hdl.handle.net/20.500.12395/22770
dc.identifier.volume46en_US
dc.identifier.wosWOS:000254237800006en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherSPRINGER HEIDELBERGen_US
dc.relation.ispartofMEDICAL & BIOLOGICAL ENGINEERING & COMPUTINGen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectnovel similarity-based weighting methoden_US
dc.subjectatherosclerosisen_US
dc.subjectcarotid arteryen_US
dc.subjectfast Fourier transformationen_US
dc.subjectWelchen_US
dc.subjectAIRSen_US
dc.subjectFuzzy-AIRSen_US
dc.subjecthybrid systemsen_US
dc.titleUsage of a novel, similarity-based weighting method to diagnose atherosclerosis from carotid artery Doppler signalsen_US
dc.typeArticleen_US

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