Machine Learning-Enabled Clinical Decision Support Database

Develop a predictive database architecture that supports machine learning model training and real-time inference for clinical decision support. Design a schema that: 1) Securely aggregates patient history, diagnostic images, lab results, and genetic data, 2) Enables dynamic feature engineering, 3) Supports model versioning and A/B testing, and 4) Provides transparent model interpretability. Include robust data lineage tracking and demonstrate how the system maintains model performance without compromising patient privacy.