Applications of Soft Set Theory in medical Diagnosis

Abstract

Soft set theory, introduced by Molodtsov in 1999, provides a flexible mathematical framework to handle uncertainty, vagueness, and incomplete information-challenges commonly faced in the medical domain.  This paper explores the application of soft set theory in medical diagnosis, where symptoms may be imprecise, overlapping, or partially observed.  By leveraging soft sets, healthcare professionals can develop more accurate and adaptable diagnostic models the study highlights a practical implementation of soft sets in diagnosing diseases based on symptom evaluation, demonstrating the effectiveness of soft decision-making approaches compared to classical methods.