Prediagnosis of Disease Based on Symptoms by Generalized Dual Hesitant Hexagonal Fuzzy Multi-Criteria Decision-Making Techniques

Abstract

Multi-criteria decision-making (MCDM) is now frequently utilized to solve difficulties in everyday life. It is challenging to rank possibilities from a set of options since this process depends on so many conflicting criteria. The current study focuses on recognizing symptoms of illness and then using an MCDM diagnosis to determine the potential disease. The following symptoms are considered in this study: fever, body aches, fatigue, chills, shortness of breath (SOB), nausea, vomiting, and diarrhea. This study shows how the generalised dual hesitant hexagonal fuzzy number (GDHHχFN) is used to diagnose disease. We also introduce a new de-fuzzification method for GDHHχFN. To diagnose a given condition, GDHHχFN coupled with MCDM tools, such as the fuzzy criteria importance through inter-criteria correlation (FCRITIC) method, is used for finding the weight of criteria. Furthermore, the fuzzy weighted aggregated sum product assessment (FWASPAS) method and a fuzzy combined compromise solution (FCoCoSo) are used to rank the alternatives. The alternative diseases are chosen to be malaria, influenza, typhoid, dengue, monkeypox, ebola, and pneumonia. A sensitivity analysis is carried out on three patients affected by different diseases to assess the validity and reliability of our methodologies.