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GAMER-MRI in Multiple Sclerosis Identifies the Diffusion-Based Microstructural Measures That Are Most Sensitive to Focal Damage: A Deep-Learning-Based Analysis and Clinico-Biological Validation.
10.3389/fnins.2021.647535
000641156900001
33889069
Lu
P.J.
author
Barakovic
M.
author
Weigel
M.
author
Rahmanzadeh
R.
author
Galbusera
R.
author
Schiavi
S.
author
Daducci
A.
author
La Rosa
F.
author
Bach Cuadra
M.
author
Sandkühler
R.
author
Kuhle
J.
author
Kappos
L.
author
Cattin
P.
author
Granziera
C.
author
article
2021
Frontiers in neuroscience
1662-4548
1662-453X
journal
15
647535
advanced quantitative diffusion MRI
clinically correlated measure selection
deep learning
multiple sclerosis
relative importance order
eng
60_published
true
peer-reviewed
Publication types: Journal Article
Publication Status: epublish
https://serval.unil.ch/notice/serval:BIB_5988DB04D91A
https://serval.unil.ch/resource/serval:BIB_5988DB04D91A.P001/REF.pdf
http://nbn-resolving.org/urn/resolver.pl?urn=urn:nbn:ch:serval-BIB_5988DB04D91A5
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