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Personalized federated learning for predicting disability progression in multiple sclerosis using real-world routine clinical data
Journal article   Open access   Peer reviewed

Personalized federated learning for predicting disability progression in multiple sclerosis using real-world routine clinical data

Ashkan Pirmani, Edward De Brouwer, Ádám Arany, Martijn Oldenhof, Antoine Passemiers, Axel Faes, Tomas Kalincik, Serkan Ozakbas, Riadh Gouider, Barbara Willekens, …
NPJ digital medicine, Vol.8(1), 478
2025
PMID: 40707601
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Published1.14 MBDownloadView
Published (Version of Record)CC BY-NC-ND V4.0 Open Access

Abstract

Machine learning Multiple sclerosis Outcomes research Predictive medicine Statistical methods

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UN Sustainable Development Goals (SDGs)

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#3 Good Health and Well-Being

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International collaboration
Citation topics
1 Clinical & Life Sciences
1.155 Medical Ethics
1.155.2774 Artificial Intelligence in Healthcare and Medicine
Web Of Science research areas
Health Care Sciences & Services
Medical Informatics
ESI research areas
Clinical Medicine
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