title: A new data preparation method based on clustering algorithms for diagnosis systems of heart and diabetes diseases.
abstract: The 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.
authors.affiliation: Electrical-Electronics Engineering Department, Engineering Faculty, Selcuk University, Konya, Turkey, nyilmaz@selcuk.edu.tr.
authors.forename: Nihat
authors.initials: N
authors.lastname: Yilmaz
authors.forename: Onur
authors.initials: O
authors.lastname: Inan
authors.forename: Mustafa Serter
authors.initials: MS
authors.lastname: Uzer
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods; D003627:Data Interpretation, Statistical; D003920:Diabetes Mellitus / Q000145:classification / Q000175:diagnosis*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D006331:Heart Diseases / Q000145:classification / Q000175:diagnosis*; D006801:Humans
references.citation: IEEE Trans Neural Netw. 2001;12(2):277-306
references.pmid: 18244384
references.citation: IEEE Trans Neural Netw. 1997;8(3):694-713
references.pmid: 18255671
references.citation: J Med Syst. 2013 Apr;37(2):9934
references.pmid: 23479268
references.citation: J Med Syst. 2012 Oct;36(5):2721-9
references.pmid: 21695498
references.citation: Artif Intell Med. 2011 Jun;52(2):59-66
references.pmid: 21600745
references.citation: J Med Syst. 2012 Oct;36(5):3011-8
references.pmid: 21912972
references.citation: J Med Syst. 2012 Aug;36(4):2141-7
references.pmid: 21547504
references.citation: IEEE Trans Inf Technol Biomed. 2009 Jul;13(4):621-8
references.pmid: 19369167