Initial Study to Evaluate Fuzzy Logic on Diagnosis of Generic Atherosclerosis

Abstract

Atherosclerosis is a disease in which plaque builds up inside the arteries that eventually intend to be hardened over time thus narrows the arteries. This work is to develop an atherosclerosis diagnosis system using fuzzy logic and to construct a prototype of atherosclerosis risk monitor. Simultaneously, the system is validated by comparing the result obtained from the system and the one from the prototype. Five membership functions are setup such as age, body mass index (BMI), intima-media thickness (IMT), blood pressure and blood glucose level, from 20 volunteers males and females. The output fuzzy sets are divided into Healthy, Low risk, Mid risk, High risk, and Very high risk. This leads to the awareness level of people thus improve the societal health. The constructed prototype is validated by inserting the data and reconfirmed the diagnosed result on the display. It showed that the prototype has 95% realibility since the output of the system is calculated with 100% low risk (LR) of atherosclerosis.