Developing Fuzzy Inference System for Disease Prediction

Abstract

Knowledge-based systems can be developed using fuzzy set theory and fuzzy logic, which are well-suited to and applicable for a wide range of medical tasks, including, but not limited to, the interpretation of sets of medical findings, the differentiation of syndromes in eastern medicine, the diagnosis of diseases in Western medicine, the mixed diagnosis of integrated western and eastern medicine, the optimal selection of medical treatments integrating western and eastern medicine, and real-time monitoring of patient data. In this research, we introduce a Fuzzy Inference System developed to aid in the processing of real-time medical diagnostics. The primary goal is to improve the quality of healthcare delivery by equipping hospital managers with a set of tools based on medical decision making processes. The goal of this method is to identify potential patient risk factors throughout the screening process. The automation of this procedure is advantageous since it allows for immediate answers that do not require the intervention of a physician (and hence may be carried out by nurses), but it also represents a loss of potential revenue for the hospital.