Deep learning to predict progression independent of relapse activity at a first demyelinating event.

ABSTRACT: Progression independent of relapse activity is the main cause of irreversible disability in multiple sclerosis and is strongly associated with older age at symptom onset. Early and accurate prediction, at symptom onset, of which patients are at highest risk of progression independent of relapses, is an unmet need. This study aimed to develop a deep learning survival model using only routine MRI acquired at the first demyelinating attack to predict the risk of progression independent of relapses, and assess its ability to improve classical age-adjusted predictions. We analysed a prospective cohort of patients under 50, clinically assessed within three months of symptom onset, with available MRI (T1- and T2-Fluid-Attenuated Inversion Recovery sequences). An independent early multiple scleros

SUBMITTER: Coll L 

PROVIDER: S-EPMC12226453 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature