Fuzzy Logic-Based Driven Model for Detection and Prediction of Diabetes Mellitus Type 2

Abstract

Diabetes is a chronic metabolic disease characterized by elevated blood sugar levels that over time cause severe damage to the heart, blood vessels, eyes, kidneys, and nerves and the most common is type 2 diabetes (T2DM). The objective of this study is to create a diabetes type 2 awareness model using a fuzzy logic machine learning tool. This model will contribute to healthy living among the population by proposing a low-cost and standalone solution, i.e., a medical expert will not be required to be physically present to interpret the results to be used in the detection and diagnosis of the disease. The solution is designed using information acquired from medical experts in diabetes treatment as well as diabetes risk factors. This information is incorporated into the model development by considering all the information and setting the rule table with various ranges as guided by the experts. This model is designed to be deployed on an edge-based device.