A New Data Preparation Method Based on Clustering Algorithms for Diagnosis Systems of Heart and Diabetes Diseases

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dc.contributor.authorYilmaz, Nihat
dc.contributor.authorInan, Onur
dc.contributor.authorUzer, Mustafa Serter
dc.date.accessioned2020-03-26T18:49:12Z
dc.date.available2020-03-26T18:49:12Z
dc.date.issued2014
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractThe most important factors that prevent pattern recognition from functioning rapidly and effectively are the noisy and inconsistent data in databases. This article presents a new data preparation method based on clustering algorithms for diagnosis of heart and diabetes diseases. In this method, a new modified K-means Algorithm is used for clustering based data preparation system for the elimination of noisy and inconsistent data and Support Vector Machines is used for classification. This newly developed approach was tested in the diagnosis of heart diseases and diabetes, which are prevalent within society and figure among the leading causes of death. The data sets used in the diagnosis of these diseases are the Statlog (Heart), the SPECT images and the Pima Indians Diabetes data sets obtained from the UCI database. The proposed system achieved 97.87 %, 98.18 %, 96.71 % classification success rates from these data sets. Classification accuracies for these data sets were obtained through using 10-fold cross-validation method. According to the results, the proposed method of performance is highly successful compared to other results attained, and seems very promising for pattern recognition applications.en_US
dc.description.sponsorshipSelcuk University Scientific Research Projects CoordinatorshipSelcuk Universityen_US
dc.description.sponsorshipThe authors are grateful to Selcuk University Scientific Research Projects Coordinatorship for support of the manuscript.en_US
dc.identifier.doi10.1007/s10916-014-0048-7en_US
dc.identifier.issn0148-5598en_US
dc.identifier.issn1573-689Xen_US
dc.identifier.issue5en_US
dc.identifier.pmid24737307en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://dx.doi.org/10.1007/s10916-014-0048-7
dc.identifier.urihttps://hdl.handle.net/20.500.12395/30554
dc.identifier.volume38en_US
dc.identifier.wosWOS:000337790600012en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherSPRINGERen_US
dc.relation.ispartofJOURNAL OF MEDICAL SYSTEMSen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectHeart and Diabetes diseasesen_US
dc.subjectSupport Vector Machineen_US
dc.subjectModified K-means Algorithmen_US
dc.titleA New Data Preparation Method Based on Clustering Algorithms for Diagnosis Systems of Heart and Diabetes Diseasesen_US
dc.typeArticleen_US

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