Machine learning to predict penumbra core mismatch in acute ischemic stroke using clinical note data

Machine learning to predict penumbra core mismatch in acute ischemic stroke using clinical note data

Abstract In acute ischemic stroke due to large-vessel occlusion (AIS-LVO), late-window endovascular thrombectomy (EVT) decisions depend on penumbra-to-core (P:C) mismatch from computed tomographic perfusion (CTP). We developed multiple machine learning (ML) models to predict P:C ratios from a retros...

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Bibliographic Details
Main Authors: Shaun Kohli, Parul Agarwal, “Andy” Ho Wing Chan, Asala Erekat, Girish Nadkarni, Benjamin Kummer
Format: Article
Language:English
Published: Nature Portfolio 2025-06-01
Series:npj Digital Medicine
Online Access:https://doi.org/10.1038/s41746-025-01703-1
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