Machine Learning Predictive Risk Assessment Model

Develop a scikit-learn based predictive model for cardiovascular disease risk using multi-source health data. Create a pipeline that integrates genetic markers, longitudinal patient records, lifestyle factors, and real-time wearable device metrics. Implement cross-validation with stratified k-fold, handle class imbalance using SMOTE, and generate a comprehensive model performance report including precision, recall, and ROC-AUC metrics.