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Quantifying Progression of Multiple Sclerosis via Classification of Depth Videos.

, , , , , , , , , , , , , , , , , , and . MICCAI (2), volume 8674 of Lecture Notes in Computer Science, page 429-437. Springer, (2014)

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Association of regional gray matter volume loss and progression of white matter lesions in multiple sclerosis - A longitudinal voxel-based morphometry study., , , , , , , , , and 3 other author(s). NeuroImage, 45 (1): 60-67 (2009)Reproducibility of fMRI in the clinical setting: Implications for trial designs., , , , , , , , , and 19 other author(s). NeuroImage, 42 (2): 603-610 (2008)Quantifying Progression of Multiple Sclerosis via Classification of Depth Videos., , , , , , , , , and 9 other author(s). MICCAI (2), volume 8674 of Lecture Notes in Computer Science, page 429-437. Springer, (2014)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]., , , , , , , , , and 31 other author(s). Comput. Methods Programs Biomed., (2022)Multivariate pattern classification of gray matter pathology in multiple sclerosis., , , , , , , , , and 1 other author(s). NeuroImage, 60 (1): 400-408 (2012)Performance of five research-domain automated WM lesion segmentation methods in a multi-center MS study., , , , , , , , , and 15 other author(s). NeuroImage, (2017)Microstructure-Weighted Connectomics in Multiple Sclerosis., , , , , , , , , and . Brain Connect., 12 (1): 6-17 (2022)Longitudinal modeling of MS patient trajectories improves predictions of disability progression., , , , , , , , , and 31 other author(s). CoRR, (2020)Short-term adaptation to a simple motor task: A physiological process preserved in multiple sclerosis., , , , , , , , , and 19 other author(s). NeuroImage, 45 (2): 500-511 (2009)Power estimation for non-standardized multisite studies., , , , , , , , , and 46 other author(s). NeuroImage, (2016)