An expert system for early diagnosis of stroke

Main Article Content

T Agenmonmen
E. I. Ihama
K. O Obahiagbon
O Eguasa

Abstract

The rate at which stroke is killing humans globally on a daily basis is becoming worrisome. Stroke is a medical emergency that needs prompt attention because it stops the supply of blood to the brain. Early detection of the disease depends on the approach/method utilized in diagnosing this disease. As such, a suitable method that can accurately detect it becomes a compelling alternative to overcome the challenges peculiar to the disease. An expert system for early diagnosis of stroke is proposed to ameliorate the challenges because it is an intelligent system that can aid physicians in managing the uncertainties associated with stroke and aid early diagnosis. This paper presents an expert system for early diagnosis of stroke that uses the human-like reasoning style, a Fuzzy Logic system to diagnose and suggest possible treatments for stroke through interactivity with user, with aim of developing an expert system and exploring the potential of fuzzy logic to assist clinicians in Nigeria to accurately predict and differentiate between the different types of stroke. It employs programs like MySQL, PHP, JAVA and XML. The system provides adequate and appropriate results and also makes reliable predictions to users.

Article Details

How to Cite
Agenmonmen , T., Ihama, E. I., Obahiagbon , K. O., & Eguasa , O. (2022). An expert system for early diagnosis of stroke. NIGERIAN JOURNAL OF SCIENCE AND ENVIRONMENT, 19(2). Retrieved from https://delsunjse.com/index.php/njse/article/view/3
Section
Articles