Machine Learning for Diabetic Foot Ulcer Prediction in Sub-Saharan Africa End-to-end ML pipeline for early DFU risk prediction using clinical data. Implements Logistic Regression, Random Forest, XGBoost with SHAP explainability. Includes synthetic data generator and reproducible validation for resource-constrained healthcare settings.