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

Diplomová práce

Anotace:

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.

Klíčová slova

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

Jazyk práce: čeština

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

Obhajoba závěrečné práce

• Vedoucí: prof. Dr. Thomas Spittler

JIHOČESKÁ UNIVERZITA V ČESKÝCH BUDĚJOVICÍCH

Přírodovědecká fakulta

Magisterský studijní program / obor:
Artificial Intelligence and Data Science / Artificial Intelligence and Data Science