Comparative Study of Fuzzy Logic, Artificial Neural Network, and Neuro-Fuzzy System in Medical Diagnostic - An Approach towards a Medical Expert System

Harvey Ngoe KOLLE

Master's thesis

Anotácia:

This study compares the performance of three artificial intelligence techniques (fuzzy logic, artificial neural networks, and neuro-fuzzy systems) in the medical diagnosis of diabetes mellitus, heart disease, and hepatitis B. Medical expert systems were developed using these techniques and evaluated on medical datasets. The results show that neuro-fuzzy systems demonstrate the best performance overall and are the most promising approach for developing accurate and efficient medical expert systems.

Abstract:

This study compares the performance of three artificial intelligence techniques (fuzzy logic, artificial neural networks, and neuro-fuzzy systems) in the medical diagnosis of diabetes mellitus, heart disease, and hepatitis B. Medical expert systems were developed using these techniques and evaluated on medical datasets. The results show that neuro-fuzzy systems demonstrate the best performance overall and are the most promising approach for developing accurate and efficient medical expert systems.

Kľúčové slová

fuzzy logic, artificial neural networks, neuro-fuzzy systems, medical diagnosis, expert system.

Jazyk práce: Czech

Datum vytvoření / odevzdání či podání práce: 6. 2. 2023

Obhajoba závěrečné práce

• Vedúci: prof. Dr. Thomas Spittler

UNIVERSITY OF SOUTH BOHEMIA IN ČESKÉ BUDĚJOVICE

Faculty of Science

Master programme / odbor:
Artificial Intelligence and Data Science / Artificial Intelligence and Data Science