Diabetes Risk
Prediction System
Powered by a novel Hybrid RF-GBDT model and 7 state-of-the-art machine learning algorithms for highly accurate diabetes risk assessment.
What You Can Do
Explore powerful tools backed by cutting-edge research
Predict Risk
Enter 8 simple health parameters and instantly receive a diabetes risk prediction from multiple ML models.
Try NowCompare Models
Explore an interactive dashboard comparing 7 ML models on accuracy, precision, recall, F1 score, and ROC-AUC.
View DashboardResearch-Backed
Built on a peer-reviewed research paper proposing a novel Hybrid RF-GBDT ensemble model for diabetes prediction.
Learn MoreAbout the Project
This system is developed as part of a B.Tech final-year research project at Raj Kumar Goel Institute of Technology. It implements a comprehensive machine-learning pipeline for diabetes risk prediction using the internationally recognized PIMA Indians Diabetes Dataset.
Seven classification algorithms are trained and compared, including traditional models, popular ensembles, and a novel Hybrid RF-GBDT model that achieves state-of-the-art accuracy.
Read the ResearchHybrid RF-GBDT Ensemble Architecture
Ready to Assess Your Diabetes Risk?
Enter your health parameters and get instant predictions from 7 ML models