Patient Risk Prediction Automated Workflow

Create an end-to-end machine learning pipeline for automated patient risk stratification that integrates electronic health records, genetic data, lifestyle information, and historical treatment outcomes. The system should: 1) Perform multi-source data ingestion, 2) Apply advanced feature engineering techniques, 3) Train predictive models with explainable AI components, 4) Generate personalized risk scores, and 5) Provide confidence interval assessments. Implement robust privacy protections and demonstrate model interpretability for clinical decision support.