Fuzzy Sets-Based Approaches for Improved Medical Diagnosis: An Analysis and Overview of Major Research Directions

Abstract

Today's sedentary lifestyle gives rise to a variety of diseases, making its accurate diagnosis quite essential so that proper treatment can be provided. Computational and artificial intelligence (AI) based approaches can be used to diagnose with better accuracy and reliability, and the process can be automated. However, medical diagnosis encompasses complex decision-making procedures that are often associated with uncertainty and imprecise information. Though fuzzy sets and systems have been effectively used for medical diagnosis, further attention is required to arrive at intelligent and expert systems for better and more accurate diagnosis. In this paper, we present a comprehensive overview of the fuzzy sets-based approaches utilized for diagnosis in the medical domain, and conduct a bibliometric analysis of the publications in fuzzy medical diagnosis.