Built a supervised ML model to predict diseases using patient medical records, achieving 72% accuracy. • Used Pandas, NumPy, and Scikit-learn to preprocess structured healthcare data. • Applied classification algorithms like RandomForest and Logistic Regression. • Visualized model outcomes and risk patterns using Power BI and Matplotlib. • Integrated with a MySQL backend and presented predictions in dashboard format.