Federated Learning-Enabled Medical Research Database

Develop a distributed database architecture supporting federated machine learning for medical research without centralizing sensitive patient data. Design a system that: 1) Enables secure model training across multiple institutions, 2) Implements differential privacy mechanisms, 3) Supports model aggregation without raw data exposure, and 4) Provides comprehensive model performance tracking. Include strategies for maintaining statistical validity and research reproducibility.