Evaluation of medical diagnosis of prostate cancer based on fuzzy TOPSIS–database interaction
Computational and Applied Mathematics, vol.42, no.7, 2023 (SCI-Expanded, Scopus)
- Publication Type: Article / Article
- Volume: 42 Issue: 7
- Publication Date: 2023
- Doi Number: 10.1007/s40314-023-02454-z
- Journal Name: Computational and Applied Mathematics
- Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Applied Science & Technology Source, Computer & Applied Sciences, zbMATH
- Keywords: Fuzzy TOPSIS, Multi-criteria decision making, Prostate cancer, Uncertainty modelling
- Kütahya Health Sciences University Affiliated: No
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.