ENHANCING DIAGNOSTIC ACCURACY IN PATHOLOGY USING FUZZY SET THEORY
Main Article Content
Keywords
Cardiovascular diagnosis, fuzzy set theory, diagnostic accuracy, uncertainty modelling, physiological measurements, fuzzy membership values
Abstract
Accurate diagnosis of cardiovascular conditions is pivotal for effective patient care and treatment planning. This study explores the application of fuzzy set theory to enhance diagnostic accuracy in cardiovascular medicine. Fuzzy sets provide a flexible framework to model uncertainty and imprecision inherent in physiological measurements. A novel diagnostic approach is proposed, incorporating fuzzy membership values to quantify the degrees of affiliation to different diagnostic categories. We present a comparative analysis of the fuzzy set-based approach against traditional methods using a dataset of heart rate, blood pressure, and cholesterol levels. Our findings demonstrate that the fuzzy set-based approach yields superior accuracy, especially in cases with overlapping features, offering a promising avenue for improving cardiovascular diagnostics. This study underscores the potential of integrating fuzzy set theory to address diagnostic challenges in medical practice
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