Proposed Intelligent Decision Support System Using Hedge Algebra Integrated with Picture Fuzzy Relations for Improvement of Decision-Making in Medical Diagnoses

Abstract

Traditional fuzzy set theory has recently demonstrated its inefficiency in handling linguistic terms directly, including the degree of neutrality in medical diagnoses. Most decision support systems in medical diagnoses are restricted since both explicit and tacit knowledge of doctors involving linguistic semantics while making decisions have not been considered in the system. Thus this paper has presented a novel approach utilizing hedge algebra and picture fuzzy sets applying for a medical decision support system. In the proposed model, picture fuzzy rule-based approach and hedge algebra using linguistic semantics are used to express rules and preferences which aims to support doctors in diagnosing patients. Experimental results in simulations for the proposed method demonstrate a high level of precision and confidence, indicating its potential utilization in medical diagnostic domain.