Privacy-Preserving AI Hits Mainstream

A 47-hospital network achieved FDA-approved breast cancer detection AI (94.3% accuracy) using the open-source APPFL framework:

Technical Innovations

Heterogeneous Model Fusion: Combines CNN (imaging) and GNN (patient graph) updates across institutions

Dynamic Weight Encryption: Homomorphic masking prevents gradient leakage attacks

Adaptive Client Selection: Prioritizes hospitals with rare subtypes (e.g., triple-negative cases)

Impact Metrics

140% larger training set vs. single-hospital models

22% higher minority group accuracy

0.7% differential privacy budget (meets HIPAA standards)