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Federated Learning in Healthcare: From Research to Real-World Deployment

NVIDIA researchers and collaborators published a review in the Annual Review of Biomedical Engineering detailing the transition of federated learning in healthcare from research to real-world deployment. The paper, authored by Spyridon Bakas, Xiaoxiao Li, Prashant Shah, and Holger Roth, examines practical applications and challenges in medical settings.

read1 min views1 publishedJun 15, 2026

Research Labs All Research Labs Spatial Intelligence Applied Research Autonomous Vehicles Deep Imagination Publications AI Playground New and Featured AI Art Gallery NGC Demos Research Areas AI & Machine Learning 3D Deep Learning Computer Vision Robotics All Areas Careers Academic Collaborations Government Collaborations Graduate Fellowship Internships Research Openings Research Scientists Meet the Team Licensing Skip to main content Artificial Intelligence Computing Leadership from NVIDIA Login Research Labs All Research Labs Spatial Intelligence Applied Research Autonomous Vehicles Deep Imagination Publications AI Playground New and Featured AI Art Gallery NGC Demos Research Areas AI & Machine Learning 3D Deep Learning Computer Vision Robotics All Areas Careers Academic Collaborations Government Collaborations Graduate Fellowship Internships Research Openings Research Scientists Meet the Team Licensing Search Search Enter the terms you wish to search for. Publications Federated Learning in Healthcare: From Research to Real-World Deployment Federated Learning in Healthcare: From Research to Real-World Deployment Authors Spyridon Bakas (Indiana University) Xiaoxiao Li (University of British Columbia) Prashant Shah (MLCommons) Holger Roth Publication Date Wednesday, January 21, 2026 Published in Annual Review of Biomedical Engineering Research Area Medical

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