Validation of Federated Unlearning on Collaborative Prostate Segmentation. - Yann Fraboni; Lucia Innocenti; Michela Antonelli; Richard Vidal; Laetitia Kameni; Sébastien Ourselin; Marco Lorenzi (ISIC/Care-AI/MedAGI/DeCaF@MICCAI, 2023)

Benchmarking Collaborative Learning Methods Cost-Effectiveness for Prostate Segmentation. - Lucia Innocenti; Michela Antonelli; Francesco Cremonesi; Kenaan Sarhan; Alejandro Granados; Vicky Goh; Sébastien Ourselin; Marco Lorenzi (PKDD/ECML Workshops (4), 2023)

Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications. - Francesco Cremonesi; Marc Vesin; Sergen Cansiz; Yannick Bouillard; Irene Balelli; Lucia Innocenti; Santiago Silva 001; Samy-Safwan Ayed; Riccardo Taiello; Laetitia Kameni; Richard Vidal; Fanny Orlhac; et al. (CoRR, 2023)

Enhancing Privacy in Federated Learning: Secure Aggregation for Real-World Healthcare Applications. - Riccardo Taiello; Sergen Cansiz; Marc Vesin; Francesco Cremonesi; Lucia Innocenti; Melek Önen; Marco Lorenzi (ISIC/iMIMIC/EARTH/DeCaF@MICCAI, 2024)

A cautionary tale on the cost-effectiveness of collaborative AI in real-world medical applications. - Francesco Cremonesi; Lucia Innocenti; Sébastien Ourselin; Vicky Goh; Michela Antonelli; Marco Lorenzi (CoRR, 2024)