cvd-ml-xai-risk-score

Reproducible machine learning pipeline for cardiovascular disease risk classification (n=68,630) comparing logistic regression and gradient-boosted models (XGBoost, LightGBM, Random Forest) with SHAP-based explainability, decision curve analysis, restricted cubic spline modeling, and subgroup validation.