Bipolar Fuzzy Soft Set Theory Applied to Medical Diagnosis

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.