Engineering Sciences

Yazarlar: Ömer AKGÖBEK, Serkan KAYA

Konular:-

DOI:10.12739/nwsaes.v6i1.5000067027

Anahtar Kelimeler:Data mining,Knowledge-discovery,Medical data mining,Classification,.

Özet: A rapid development and growing use of database systems, and the importance of information stored in these systems raise the issue of how to make the best use of these systems. One of the leading area where the database systems are mostly used is 'medicine'. Today, all patients' laboratory results, patient history as well as x-ray images and more are kept in databases. These of the traditional database query and report methods to filter information and to present reports does not always provide the important hidden rules contained in the stored data. Therefore, the use of data mining techniques used for knowledge discovery in this area from databases is inevitable. In this study, the rules base is created thorough the knowledge discovery by employing REX-1 algorithm, a data mining technique, on the Wisconsin Breast Cancer, Ljubljana Breast Cancer, Dermatology, Hepatitis and Diabetes sample sets, which are real life data and commonly used in the medical field. In terms of the accuracy rate, the results of this study were compared to the results of the algorithms widely used in this field, such as C4.5, NavieBayes, PART, CN2, CORE, GA-SVM.

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