2 papers
cs.LG2024
A cautionary tale on the cost-effectiveness of collaborative AI in real-world medical applications
Francesco Cremonesi, Lucia Innocenti, Sebastien Ourselin +3
Background. Federated learning (FL) has gained wide popularity as a collaborative learning paradigm enabling collaborative AI in sensitive healthcare applications. Nevertheless, th…
cs.CR2024
Enhancing Privacy in Federated Learning: Secure Aggregation for Real-World Healthcare Applications
Riccardo Taiello, Sergen Cansiz, Marc Vesin +4
Deploying federated learning (FL) in real-world scenarios, particularly in healthcare, poses challenges in communication and security. In particular, with respect to the federated…