Machine Learning Risk Prediction Model for Chronic Diseases

Architect a scalable machine learning pipeline that predicts patient risk for chronic diseases using heterogeneous medical data sources. Develop a feature engineering approach that can integrate electronic health records, genetic markers, lifestyle data, and real-time wearable device metrics. Implement cross-validation strategies that account for medical data imbalances, and create an interpretable model that provides confidence intervals and explainable risk factors.