AI-Based Diabetes Risk Detection and Monitoring System

Abstract

Diabetes is a chronic disease that requires early prediction and continuous monitoring. This paper proposes an AI-based diabetes risk detection and monitoring system using machine learning algorithms such as Logistic Regression, Decision Tree, Support Vector Machine, and Random Forest. The system predicts diabetes risk using patient parameters including glucose level, BMI, age, blood pressure, insulin, and family history. The proposed model aims to improve prediction accuracy and support preventive healthcare.