Real-Time Patient Risk Prediction Machine Learning Pipeline

Develop a scalable machine learning pipeline that can ingest multiple heterogeneous medical data sources (EHR, wearable device streams, lab results) and generate real-time risk prediction models for chronic disease progression. Implement feature engineering techniques that handle missing data, create robust cross-validation strategies, and produce interpretable risk scores with confidence intervals. The solution must support dynamic model retraining and handle GDPR/HIPAA data privacy requirements.