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Leveraging electronic health records data to predict multiple sclerosis disease activity.

Yuri AhujaNicole KimLiang LiangTianrun CaiKumar DahalThany SeyokChen LinSean FinanKatherine LiaoGuergana SavovoaTanuja ChitinisTianxi CaiZongqi Xia
Published in: Annals of clinical and translational neurology (2021)
Our novel machine-learning algorithm predicts 1-year MS relapse with accuracy comparable to other clinical prediction tools and has applicability at the point of care. This EHR-based two-stage approach of outcome prediction may have application to neurological disease beyond MS.
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