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Oliver Gerlach

Showing results (21-30 of 54) with videos related to

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Computer Methods and Programs in Biomedicine|November 8, 2021
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]Edward De Brouwer, Thijs Becker, Yves Moreau, et al.
Multiple Sclerosis (Houndmills, Basingstoke, England)|April 4, 2022
Multiple Sclerosis Severity Score (MSSS) improves the accuracy of individualized prediction in MSTomas Kalincik, Ilya Kister, Tamar E Bacon, et al.
Journal of Neurology, Neurosurgery, and Psychiatry|December 6, 2024
Disease-modifying treatment and disability progression in subclasses of patients with primary progressive MS: results from the Big MS Data NetworkJohannes Lorscheider, Alessio Signori, Suvitha Subramaniam, et al.
Journal of Neurology, Neurosurgery, and Psychiatry|October 29, 2025
Moderate-high efficacy disease-modifying therapies reduce relapse risk in late-onset multiple sclerosisYi Chao Foong, Daniel Merlo, Melissa Gresle, et al.
Journal of Neurology, Neurosurgery, and Psychiatry|September 28, 2022
Heterogeneity on long-term disability trajectories in patients with secondary progressive MS: a latent class analysis from Big MS Data networkAlessio Signori, Johannes Lorscheider, Sandra Vukusic, et al.
Multiple Sclerosis (Houndmills, Basingstoke, England)|July 7, 2025
Four years on: Pregnancy and birth outcomes reported in the MSBase pregnancy, neonatal outcomes, and Women's Health Registry (2020-2024)Vilija G Jokubaitis, Raed Alroughani, Ayse Altintas, et al.
Computer Methods and Programs in Biomedicine|June 19, 2021
Longitudinal machine learning modeling of MS patient trajectories improves predictions of disability progressionEdward De Brouwer, Thijs Becker, Yves Moreau, et al.
Computer Methods and Programs in Biomedicine|February 18, 2025
Explainable time-to-progression predictions in multiple sclerosisRobbe D'hondt, Klest Dedja, Sofie Aerts, et al.
JAMA Neurology|June 5, 2023
Comparison Between Dimethyl Fumarate, Fingolimod, and Ocrelizumab After Natalizumab CessationChao Zhu, Tomas Kalincik, Dana Horakova, et al.
Journal of Neurology, Neurosurgery, and Psychiatry|April 3, 2024
Routine CSF parameters as predictors of disease course in multiple sclerosis: an MSBase cohort studyCathérine Dekeyser, Matthias Hautekeete, Melissa Cambron, et al.
Pageof 6

Showing results (21-30 of 54) with videos related to

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Pageof 6
Computer Methods and Programs in Biomedicine|November 8, 2021
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]Edward De Brouwer, Thijs Becker, Yves Moreau, et al.
Multiple Sclerosis (Houndmills, Basingstoke, England)|April 4, 2022
Multiple Sclerosis Severity Score (MSSS) improves the accuracy of individualized prediction in MSTomas Kalincik, Ilya Kister, Tamar E Bacon, et al.
Journal of Neurology, Neurosurgery, and Psychiatry|December 6, 2024
Disease-modifying treatment and disability progression in subclasses of patients with primary progressive MS: results from the Big MS Data NetworkJohannes Lorscheider, Alessio Signori, Suvitha Subramaniam, et al.
Journal of Neurology, Neurosurgery, and Psychiatry|October 29, 2025
Moderate-high efficacy disease-modifying therapies reduce relapse risk in late-onset multiple sclerosisYi Chao Foong, Daniel Merlo, Melissa Gresle, et al.
Journal of Neurology, Neurosurgery, and Psychiatry|September 28, 2022
Heterogeneity on long-term disability trajectories in patients with secondary progressive MS: a latent class analysis from Big MS Data networkAlessio Signori, Johannes Lorscheider, Sandra Vukusic, et al.
Multiple Sclerosis (Houndmills, Basingstoke, England)|July 7, 2025
Four years on: Pregnancy and birth outcomes reported in the MSBase pregnancy, neonatal outcomes, and Women's Health Registry (2020-2024)Vilija G Jokubaitis, Raed Alroughani, Ayse Altintas, et al.
Computer Methods and Programs in Biomedicine|June 19, 2021
Longitudinal machine learning modeling of MS patient trajectories improves predictions of disability progressionEdward De Brouwer, Thijs Becker, Yves Moreau, et al.
Computer Methods and Programs in Biomedicine|February 18, 2025
Explainable time-to-progression predictions in multiple sclerosisRobbe D'hondt, Klest Dedja, Sofie Aerts, et al.
JAMA Neurology|June 5, 2023
Comparison Between Dimethyl Fumarate, Fingolimod, and Ocrelizumab After Natalizumab CessationChao Zhu, Tomas Kalincik, Dana Horakova, et al.
Journal of Neurology, Neurosurgery, and Psychiatry|April 3, 2024
Routine CSF parameters as predictors of disease course in multiple sclerosis: an MSBase cohort studyCathérine Dekeyser, Matthias Hautekeete, Melissa Cambron, et al.
Pageof 6