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"Longitudinal machine learning modeling of MS patient trajectories improves ..."
Edward De Brouwer et al. (2021)
- Edward De Brouwer
, Thijs Becker
, Yves Moreau
, Eva Kubala Havrdova
, Maria Trojano, Sara Eichau, Serkan Ozakbas, Marco Onofrj, Pierre Grammond
, Jens Kuhle
, Ludwig Kappos, Patrizia Sola
, Elisabetta Cartechini, Jeannette Lechner-Scott
, Raed Alroughani, Oliver Gerlach, Tomas Kalincik, Franco Granella, Francois Grand'Maison, Roberto Bergamaschi, Maria Jose Sa, Bart Van Wijmeersch, Aysun Soysal
, Jose Luis Sanchez-Menoyo, Claudio Solaro, Cavit Boz, Gerardo Iuliano
, Katherine Buzzard, Eduardo Aguera-Morales
, Murat Terzi, Tamara Castillo Trivio
, Daniele Spitaleri
, Vincent Van Pesch
, Vahid Shaygannejad, Fraser Moore, Celia Oreja Guevara
, Davide Maimone, Riadh Gouider
, Tunde Csepany, Cristina Ramo-Tello
, Liesbet M. Peeters
:
Longitudinal machine learning modeling of MS patient trajectories improves predictions of disability progression. Comput. Methods Programs Biomed. 208: 106180 (2021)
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