Symptom based Hierarchical Classification of Diabetes and Thyroid disorders using Fuzzy Cognitive Maps

TL;DR

This paper proposes a hierarchical Fuzzy Cognitive Maps-based system for classifying diabetes and thyroid disorders, capturing complex interrelations among symptoms to improve medical decision support.

Contribution

It introduces a novel hierarchical FCM approach specifically designed for classifying diabetes and thyroid disorders and their subtypes.

Findings

Effective classification of diabetes and thyroid disorders

Hierarchical FCM captures complex symptom interactions

Potential for improved medical decision support

Abstract

Fuzzy Cognitive Maps (FCMs) are soft computing technique that follows an approach similar to human reasoning and human decision-making process, making them a valuable modeling and simulation methodology. Medical Decision Systems are complex systems consisting of many factors that may be complementary, contradictory, and competitive; these factors influence each other and determine the overall diagnosis with a different degree. Thus, FCMs are suitable to model Medical Decision Support Systems. The proposed work therefore uses FCMs arranged in hierarchical structure to classify between Diabetes, Thyroid disorders and their subtypes. Subtypes include type 1 and type 2 for diabetes and hyperthyroidism and hypothyroidism for thyroid.