EN
Bipolar Fuzzy Soft Set Theory Applied to Medical Diagnosis
Abstract
The primary objective of this study is to advance Sanchez’s method for medical diagnosis by incorporating fuzzy arithmetic operations. To achieve this, we generalize the existing approach through the application of bipolar fuzzy soft set theory, which enables the identification of two distinct types of medical knowledge within a unified framework. Additionally, we propose a novel decision-making algorithm tailored to this enhanced approach. The application of this algorithm in the medical field is illustrated through practical examples, demonstrating its potential to improve diagnostic processes and decision-making in medical practice.
Keywords
References
- Abdullah, S., Aslam, M., Ullah, K., Bipolar fuzzy soft sets and its applications in decision making problem, Journal of Intelligent and Fuzzy Systems, 27(2)(2014), 729–742.
- Chetia, B., Das, P.K., An application of interval valued fuzzy soft set in medical diagnosis, International Journal of Contemporary Mathematical Sciences, 5(38)(2010), 1887–1894.
- Çelik, Y., Yamak S., Fuzzy soft set theory applied to medical diagnosis using fuzzy arithmetic operations, Journal of Inequalities and Applications, 82(2013), 1–9.
- Dalkılıç, O., novel approach to soft set theory in decision-making under uncertainty, International Journal of Computer Mathematics, 98(2021)(10), 1935–1945.
- Dalkılıç, O., Relations on neutrosophic soft set and their application in decision making, Journal of Applied Mathematics and Computing, 67(2021), 257-–273.
- Dalkılıç, O., Approaches that take into account interactions between parameters: pure (fuzzy) soft sets, International Journal of Computer Mathematics, 99(2022)(7), 1428–1437.
- Dalkılıç, O., Two novel approaches that reduce the effectiveness of the decision maker in decision making under uncertainty environments, Iranian Journal of Fuzzy Systems, 19(2022)(2), 105–117.
- De, S.K., Biswas, R., Roy, A.R., An application of intuitionistic fuzzy sets in medical diagnosis, Fuzzy Sets Systems, 117(2001), 209–213.
Details
Primary Language
English
Subjects
Mathematical Sciences
Journal Section
Research Article
Publication Date
December 31, 2024
Submission Date
February 22, 2023
Acceptance Date
September 3, 2024
Published in Issue
Year 2024 Volume: 16 Number: 2
APA
Dalkılıç, O., & Demirtaş, N. (2024). Bipolar Fuzzy Soft Set Theory Applied to Medical Diagnosis. Turkish Journal of Mathematics and Computer Science, 16(2), 314-324. https://doi.org/10.47000/tjmcs.1254943
AMA
1.Dalkılıç O, Demirtaş N. Bipolar Fuzzy Soft Set Theory Applied to Medical Diagnosis. TJMCS. 2024;16(2):314-324. doi:10.47000/tjmcs.1254943
Chicago
Dalkılıç, Orhan, and Naime Demirtaş. 2024. “Bipolar Fuzzy Soft Set Theory Applied to Medical Diagnosis”. Turkish Journal of Mathematics and Computer Science 16 (2): 314-24. https://doi.org/10.47000/tjmcs.1254943.
EndNote
Dalkılıç O, Demirtaş N (December 1, 2024) Bipolar Fuzzy Soft Set Theory Applied to Medical Diagnosis. Turkish Journal of Mathematics and Computer Science 16 2 314–324.
IEEE
[1]O. Dalkılıç and N. Demirtaş, “Bipolar Fuzzy Soft Set Theory Applied to Medical Diagnosis”, TJMCS, vol. 16, no. 2, pp. 314–324, Dec. 2024, doi: 10.47000/tjmcs.1254943.
ISNAD
Dalkılıç, Orhan - Demirtaş, Naime. “Bipolar Fuzzy Soft Set Theory Applied to Medical Diagnosis”. Turkish Journal of Mathematics and Computer Science 16/2 (December 1, 2024): 314-324. https://doi.org/10.47000/tjmcs.1254943.
JAMA
1.Dalkılıç O, Demirtaş N. Bipolar Fuzzy Soft Set Theory Applied to Medical Diagnosis. TJMCS. 2024;16:314–324.
MLA
Dalkılıç, Orhan, and Naime Demirtaş. “Bipolar Fuzzy Soft Set Theory Applied to Medical Diagnosis”. Turkish Journal of Mathematics and Computer Science, vol. 16, no. 2, Dec. 2024, pp. 314-2, doi:10.47000/tjmcs.1254943.
Vancouver
1.Orhan Dalkılıç, Naime Demirtaş. Bipolar Fuzzy Soft Set Theory Applied to Medical Diagnosis. TJMCS. 2024 Dec. 1;16(2):314-2. doi:10.47000/tjmcs.1254943
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