A Study on diagnosis of infectious diseases by using fuzzy soft sets

Abstract

Fuzzy soft set theory constitutes a sophisticated mathematical paradigm that integrates the initial principles of both fuzzy sets and soft sets. This amalgamation furnishes a robust methodological approach for tackling the intricacies associated with uncertainty and doubt within multipart systems. Considered to transcend the constraints inherent in conventional and fuzzy set theories, fuzzy soft sets significantly augment decision-making processes by concurrently assimilating degrees of membership and parameterized attributes. newlineThe efficiency of this theory is predicated on its capacity to manage contexts wherein data uncertainty and attribute vagueness are concurrently present. In contrast to traditional fuzzy sets, which prioritize membership grades exclusively, fuzzy soft sets incorporate parameterization, thereby enhancing their versatility for practical applications. This distinctive feature renders them particularly potent in domains such as decision-making, data analysis, and medical diagnostics. Moreover, fuzzy soft sets facilitate a diverse array of operations and aggregation techniques, permitting their application within complex environments including multi-criteria decision-making and information retrieval systems. As a result, fuzzy soft set theory has achieved substantial acceptance across various disciplines characterized by inherent imprecision and uncertainty, solidifying its role as a fundamental component in contemporary computational and mathematical endeavours. newlineWithin the realm of medical sciences, fuzzy soft set theory has emerged as a transformative instrument for navigating the intricacies associated with diagnostic processes. This framework enables the management of uncertainties and ambiguities that are prevalent in medical datasets. Recent scholarly investigations underscore the theoretical advancements and practical utilities of fuzzy soft set models in medical diagnostics, illustrating their potential to enhance decision-making processes within healthcare settings. newlineIn this study a nota