Federated Machine Learning API for Medical Diagnostics

Architect a distributed API framework that enables secure, privacy-preserving machine learning model training across multiple healthcare institutions without directly sharing patient data. Implement a protocol that supports model parameter aggregation, differential privacy mechanisms, and cryptographic verification to ensure no raw patient information is ever transmitted. Include performance metrics tracking, model versioning, and a mechanism for institutional consent and participation management.