Comparing Poor and Favorable Outcome Prediction With Machine Learning After Mechanical Thrombectomy in Acute Ischemic Stroke

Comparing Poor and Favorable Outcome Prediction With Machine Learning After Mechanical Thrombectomy in Acute Ischemic Stroke

Background and PurposeOutcome prediction after mechanical thrombectomy (MT) in patients with acute ischemic stroke (AIS) and large vessel occlusion (LVO) is commonly performed by focusing on favorable outcome (modified Rankin Scale, mRS 0–2) after 3 months but poor outcome representing severe disabi...

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Bibliographic Details
Main Authors: Matthias A. Mutke, Vince I. Madai, Adam Hilbert, Esra Zihni, Arne Potreck, Charlotte S. Weyland, Markus A. Möhlenbruch, Sabine Heiland, Peter A. Ringleb, Simon Nagel, Martin Bendszus, Dietmar Frey
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-05-01
Series:Frontiers in Neurology
Subjects:
stroke
mechanical thrombectomy
outcome prediction
machine learning
MRI
perfusion imaging
Online Access:https://www.frontiersin.org/articles/10.3389/fneur.2022.737667/full

Internet

https://www.frontiersin.org/articles/10.3389/fneur.2022.737667/full

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