CONSISTENCY MEASUREMENT USING THE ARTIFICIAL NEURAL NETWORK OF THE RESULTS OBTAINED WITH FUZZY TOPSIS METHOD FOR THE DIAGNOSIS OF PROSTATE CANCER

CONSISTENCY MEASUREMENT USING THE ARTIFICIAL NEURAL NETWORK OF THE RESULTS OBTAINED WITH FUZZY TOPSIS METHOD FOR THE DIAGNOSIS OF PROSTATE CANCER

N. Demirtaş, O. Dalkılıç

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Abstract

In recent years great attention has been paid to studies on artificial intelli- gence since it can be applied easily to several areas like medical diagnosis, engineering and economics, among others. In this paper we present an example in medicine which aims to diagnose the patients with high prostate cancer risk using a multi-criteria decision making method.Our datas set is prostate specific antigen (PSA), free prostate specific antigen (fPSA), prostate volume (PV) and age factors of 78 patients from Necmettin Erbakan University Meram Medicine Faculty. An artificial neural network related to the consistency of convergence coefficients calculated by the Fuzzy TOPSIS method [32] is established.Thus, we understand the accuracy of the results from the Fuzzy TOPSIS method.

Keywords

Artificial neural network, Multi-criteria decision making, Prostate cancer, Fuzzy TOPSIS Method.