Sinem Sav

Privacy Leakage in Federated Learning in Radiology Reports: A Comparative Evaluation of Tokenizer-Driven Privacy Risks

Santhosh Parampottupadam, Andres Martinez, Dimitrios Bounias, Sinem Sav, Klaus Maier-Hein, Ralf Floca

Federated learning (FL) enables multi-institutional training on clinical text without sharing raw data, but gradient inversion can reconstruct sensitive information from shared model updates. The extent of this leakage for radiology reports, and the role of tokenizer design, rema…Read more