Federated Learning for Privacy-Preserving Multi-Center Clinical Trials

Abstract

This study introduces a federated learning framework enabling collaborative model training across 15 medical centers without sharing patient data. Applied to predicting ICU readmission risk, our approach achieved AUC scores comparable to centralized models while maintaining full HIPAA compliance.

Keywords: federated learning, privacy, clinical trials, machine learning