RT Journal Article
T1 Corrigendum to Longitudinal machine learning modeling of MS patient trajectories improves predictions of disability progression: [Computer Methods and Programs in Biomedicine, Volume 208, (September 2021) 106180].
A1 De Brouwer, Edward
A1 Becker, Thijs
A1 Moreau, Yves
A1 Havrdova, Eva Kubala
A1 Trojano, Maria
A1 Eichau, Sara
A1 Ozakbas, Serkan
A1 Onofrj, Marco
A1 Grammond, Pierre
A1 Kuhle, Jens
A1 Kappos, Ludwig
A1 Sola, Patrizia
A1 Cartechini, Elisabetta
A1 Lechner-Scott, Jeannette
A1 Alroughani, Raed
A1 Gerlach, Oliver
A1 Kalincik, Tomas
A1 Granella, Franco
A1 Grand'Maison, Francois
A1 Bergamaschi, Roberto
A1 Sá, Maria José
A1 Van Wijmeersch, Bart
A1 Soysal, Aysun
A1 Sanchez-Menoyo, Jose Luis
A1 Solaro, Claudio
A1 Boz, Cavit
A1 Iuliano, Gerardo
A1 Buzzard, Katherine
A1 Aguera-Morales, Eduardo
A1 Terzi, Murat
A1 Trivio, Tamara Castillo
A1 Spitaleri, Daniele
A1 Van Pesch, Vincent
A1 Shaygannejad, Vahid
A1 Moore, Fraser
A1 Oreja-Guevara, Celia
A1 Maimone, Davide
A1 Gouider, Riadh
A1 Csepany, Tunde
A1 Ramo-Tello, Cristina
A1 Peeters, Liesbet
YR 2021
FD 2021-11-05
LK http://hdl.handle.net/10668/22137
UL http://hdl.handle.net/10668/22137
LA en
DS RISalud
RD Apr 19, 2025