Diabetes Risk Prediction Model

Built a predictive healthcare model to assess diabetes risk based on clinical and demographic indicators. The project focused on data standardization, supervised classification, and rigorous model evaluation to ensure reliable predictions. By leveraging machine learning classification techniques, the solution supports early risk identification and highlights how AI can assist preventive healthcare strategies. The project emphasizes interpretability, accuracy, and practical relevance in medical decision-support systems.