Assessment of Thyroid Disorder Prevalence using Fuzzy AHP and Fuzzy TOPSIS Methods

This study applies advanced multi-criteria decision making (MCDM technique Fuzzy Analytic Hierarchy Process (Fuzzy AHP) and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) to analyse the prevalence and symptomatology of various thyroid disorders. The primary objective is to identify the most prominent symptoms and to evaluate the comparative occurrence of hypothyroidism and hyperthyroidism. Using Fuzzy AHP, symptoms were ranked based on expert evaluations, and the analysis revealed that a swollen neck is the most significant and commonly reported symptom among thyroid patients. Subsequently, Fuzzy TOPSIS was employed to assess and compare the prevalence of thyroid conditions, with findings indicating that hypothyroidism is more widespread than hyperthyroidism across the studied population. The integration of fuzzy logic into traditional MCDM methods provides a robust and nuanced framework for handling uncertainty and subjectivity in medical data, offering valuable insights for clinical diagnosis, early detection, and targeted treatment planning of thyroid-related disorders.