Privacy-Preserving Machine Learning (PPML) Inference for Clinically Actionable Models

This work introduces a secure framework for running clinically actionable ML models under homomorphic encryption. The system achieves high accuracy while ensuring full data privacy, demonstrated with healthcare datasets.