Development and validation of an explainable machine learning prediction model of hemorrhagic transformation after intravenous thrombolysis in stroke

ObjectiveTo develop and validate an explainable machine learning (ML) model predicting the risk of hemorrhagic transformation (HT) after intravenous thrombolysis.MethodsWe retrospectively enrolled patients who received intravenous tissue plasminogen activator (IV-tPA) thrombolysis within 4.5 h after...

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Autors principals:	Yanan Lin, Yan Li, Yayin Luo, Jie Han
Format:	Artigo
Idioma:	Inglês
Publicat:	Frontiers Media S.A. 2025-01-01
Col·lecció:	Frontiers in Neurology
Matèries:	acute ischemic stroke intravenous thrombolysis hemorrhagic transformation machine learning explainability
Accés en línia:	https://www.frontiersin.org/articles/10.3389/fneur.2024.1446250/full
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