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Longitudinal modeling of MS patient trajectories improves predictions of
  disability progression

Longitudinal modeling of MS patient trajectories improves predictions of disability progression

9 November 2020
E. Brouwer
Thijs Becker
Yves Moreau
E. Havrdová
M. Trojano
S. Eichau
S. Ozakbas
M. Onofrj
P. Grammond
J. Kuhle
L. Kappos
P. Sola
E. Cartechini
J. Lechner-Scott
R. Alroughani
O. Gerlach
T. Kalincik
F. Granella
Francois Granďmaison
R. Bergamaschi
M. Sá
B. Wijmeersch
A. Soysal
J. Sánchez-Menoyo
C. Solaro
C. Boz
G. Iuliano
K. Buzzard
E. Aguera-Morales
M. Terzi
Tamara Castillo Trivio
D. Spitaleri
V. Pesch
Vahid Shaygannej
F. Moore
C. O. Guevara
D. Maimone
R. Gouider
T. Csépány
C. Ramo-Tello
L. Peeters
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Papers citing "Longitudinal modeling of MS patient trajectories improves predictions of disability progression"

1 / 1 papers shown
Title
Learning Spatio-Temporal Model of Disease Progression with NeuralODEs
  from Longitudinal Volumetric Data
Learning Spatio-Temporal Model of Disease Progression with NeuralODEs from Longitudinal Volumetric Data
Dmitrii Lachinov
A. Chakravarty
C. Grechenig
U. Schmidt-Erfurth
Hrvoje Bogunović
30
11
0
08 Nov 2022
1