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Evaluation of medical diagnosis of prostate cancer based on fuzzy TOPSIS–database interaction

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Abstract

One of the most preferred methods for obtaining near-ideal results for decision-making processes is the fuzzy TOPSIS approach. However, the similarity of the closeness coefficients obtained based on this approach may increase the possible error. The aim of this article is to overcome this inadequacy based on the fuzzy TOPSIS approach and to develop the decision-making network. For this, a novel approach that interprets the closeness coefficients based on the fuzzy TOPSIS–database interaction is proposed. To test the success of this novel approach, a decision-making problem based on the diagnosis of prostate cancer, the second most common cause of death in men, is considered. In order to detect this cancer, a program has been developed for biopsy which is the final test applied by doctors. Finally, the results of this program are comparatively analyzed for fuzzy TOPSIS and the proposed novel approach.

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Acknowledgements

We are thankful to Professor Dr. I. Unal Sert for letting us share the data set taken from the Urology Department in Medicine Faculty at Necmettin Erbakan University.

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  1. Department of Mathematics, Mersin University, Mersin, Turkey

    Naime Demirtaş & Orhan Dalkılıç

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  1. Naime Demirtaş
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  2. Orhan Dalkılıç
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Correspondence to Orhan Dalkılıç.

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Communicated by Graçaliz Pereira Dimuro.

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Demirtaş, N., Dalkılıç, O. Evaluation of medical diagnosis of prostate cancer based on fuzzy TOPSIS–database interaction. Comp. Appl. Math. 42, 316 (2023). https://doi.org/10.1007/s40314-023-02454-z

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