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Fingerprint-based Diabetes Risk Prediction using XGBoost and Fuzzy Logic

IT IS A NORMAL DIABETES PREDICTION PROJECT USING ML AND FUZZY LOGIC. THE ML PART CLASSIFY THE POSITIVE OR NEGATIVE DIABETES. ON OTHER HAND FUZZY LOGIC EXPLAIN THE RISK FACTOR.

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Adaptive Neuro-Fuzzy Inference System (ANFIS) for diabetes prediction using Python. Combines fuzzy logic and neural networks to handle uncertainty and learn from medical data effectively.

Web-based Diabetes Risk Prediction Dashboard using Flask, Machine Learning, and Fuzzy Logic with personalized health recommendations and professional dark-themed UI.

This project is a Machine Learning-based medical prediction system that predicts Diabetes and Heart Disease using supervised learning techniques. The main objective of this project is to build an intelligent and interpretable medical prediction system by combining Machine Learning with optimization and fuzzy logic techniques.