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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Detalles Bibliográficos

Autores principales:	Shaun Kohli, Parul Agarwal, “Andy” Ho Wing Chan, Asala Erekat, Girish Nadkarni, Benjamin Kummer
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	Nature Portfolio 2025-06-01
Colección:	npj Digital Medicine
Acceso en línea:	https://doi.org/10.1038/s41746-025-01703-1
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