An expert system approach based on principal component analysis and adaptive neuro-fuzzy inference system to diagnosis of diabetes disease

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dc.contributor.authorPolat, Kemal
dc.contributor.authorGuenes, Salih
dc.date.accessioned2020-03-26T17:16:59Z
dc.date.available2020-03-26T17:16:59Z
dc.date.issued2007
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractDiabetes occurs when a body is unable to produce or respond properly to insulin which is needed to regulate glucose (sugar). Besides contributing to heart disease, diabetes also increases the risks of developing kidney disease, blindness, nerve damage, and blood vessel damage. In this paper, we have detected on diabetes disease, which is a very common and important disease using principal component analysis (PCA) and adaptive neuro-fuzzy inference system (ANFIS). The aim of this study is to improve the diagnostic accuracy of diabetes disease combining PCA and ANFIS. The proposed system has two stages. In the first stage, dimension of diabetes disease dataset that has 8 features is reduced to 4 features using principal component analysis. In the second stage, diagnosis of diabetes disease is conducted via adaptive neuro-fuzzy inference system classifier. We took the diabetes disease dataset used in our study from the UCI (from Department of Information and Computer Science, University of California) Machine Learning Database. The obtained classification accuracy of our system was 89.47% and it was very promising with regard to the other classification applications in literature for this problem. (c) 2006 Elsevier Inc. All rights reserved.en_US
dc.identifier.doi10.1016/j.dsp.2006.09.005en_US
dc.identifier.endpage710en_US
dc.identifier.issn1051-2004en_US
dc.identifier.issue4en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage702en_US
dc.identifier.urihttps://dx.doi.org/10.1016/j.dsp.2006.09.005
dc.identifier.urihttps://hdl.handle.net/20.500.12395/21209
dc.identifier.volume17en_US
dc.identifier.wosWOS:000247899300003en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherACADEMIC PRESS INC ELSEVIER SCIENCEen_US
dc.relation.ispartofDIGITAL SIGNAL PROCESSINGen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectPCAen_US
dc.subjectANFISen_US
dc.subjectdiabetes diseaseen_US
dc.subjectexpert systemen_US
dc.subjectmedical diagnosisen_US
dc.titleAn expert system approach based on principal component analysis and adaptive neuro-fuzzy inference system to diagnosis of diabetes diseaseen_US
dc.typeArticleen_US

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