Explainable time-to-progression predictions in multiple sclerosis. - Robbe D'hondt; Klest Dedja; Sofie Aerts; Bart Van Wijmeersch; Tomas Kalincik; Stephen Reddel; Eva Kubala Havrdova; Alessandra Lugaresi; Bianca Weinstock-Guttman; Saloua Mrabet; Patrice Lalive; Allan G. Kermode; et al. (Comput. Methods Programs Biomed., 2025)

Personalized federated learning for predicting disability progression in multiple sclerosis using real-world routine clinical data. - Ashkan Pirmani; Edward De Brouwer; Adam Arany; Martijn Oldenhof; Antoine Passemiers; Axel Faes; Tomas Kalincik; Serkan Ozakbas; Riadh Gouider; Barbara Willekens; Dana Horáková; Eva Kubala Havrdova; et al. (npj Digit. Medicine, 2025)

Monitoring morphometric drift in lifelong learning segmentation of the spinal cord. - Enamundram Naga Karthik; Sandrine Bédard; Jan Valosek; Christoph S. Aigner; Elise Bannier; Josef Bednarík; Virginie Callot; Anna J. E. Combes; Armin Curt; Gergely Dávid; Falk Eippert; Lynn Farner; et al. (CoRR, 2025)