Longitudinal machine learning modeling of MS patient trajectories improves predictions of disability progression
- Resource Type
- Article
- Authors
- De Brouwer, Edward; Becker, Thijs; Moreau, Yves; Havrdova, Eva Kubala; Trojano, Maria; Eichau, Sara; Ozakbas, Serkan; Onofrj, Marco; Grammond, Pierre; Kuhle, Jens; Kappos, Ludwig; Sola, Patrizia; Cartechini, Elisabetta; Lechner-Scott, Jeannette; Alroughani, Raed; Gerlach, Oliver; Kalincik, Tomas; Granella, Franco; Grand'Maison, Francois; Bergamaschi, Roberto; José Sá, Maria; Van Wijmeersch, Bart; Soysal, Aysun; Sanchez-Menoyo, Jose Luis; Solaro, Claudio; Boz, Cavit; Iuliano, Gerardo; Buzzard, Katherine; Aguera-Morales, Eduardo; Terzi, Murat; Trivio, Tamara Castillo; Spitaleri, Daniele; Van Pesch, Vincent; Shaygannejad, Vahid; Moore, Fraser; Oreja-Guevara, Celia; Maimone, Davide; Gouider, Riadh; Csepany, Tunde; Ramo-Tello, Cristina; Peeters, Liesbet
- Source
- In Computer Methods and Programs in Biomedicine September 2021 208
- Subject
- Language
- ISSN
- 0169-2607