Federated learning for predicting clinical outcomes in patients with COVID-19

Researchers at NVIDIA and Harvard Medical School used federated learning to predict clinical outcomes in COVID-19 patients, enabling collaborative model training across institutions without sharing sensitive data. The study, published in Nature Medicine, demonstrated improved prediction accuracy for patient deterioration and mortality.

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 for predicting clinical outcomes in patients with COVID-19 Federated learning for predicting clinical outcomes in patients with COVID-19 Authors Ittai Dayan MGH Radiology and Harvard Medical School, Boston, MA, USA Holger Roth et al. Publication Date Wednesday, September 15, 2021 Published in Nature Medicine Research Area Medical