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Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications

Francesco Cremonesi, Marc Vesin, Sergen Cansiz, Yannick Bouillard, Irène Balelli, Lucia Innocenti, Riccardo Taiello, Santiago Silva, Samy-Safwan Ayed, Melek Önen, Fanny Orlhac, Christophe Nioche, Bastien Houis, Romain Modzelewski, Nathan Lapel, Renaud Schiappa, Olivier Humbert, Marco Lorenzi

2025Studies in computational intelligence8 citationsDOIOpen Access PDF

Topics & Concepts

Health careComputer scienceOpen sourceReal world dataHuman–computer interactionBusinessData scienceOperating systemEconomicsEconomic growthSoftwarePrivacy-Preserving Technologies in DataArtificial Intelligence in Healthcare and EducationCryptography and Data Security
Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications | Litcius