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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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Principais autores: Yanan Lin, Yan Li, Yayin Luo, Jie Han
Formato: Artigo
Idioma:Inglês
Publicado em: Frontiers Media S.A. 2025-01-01
coleção:Frontiers in Neurology
Assuntos:
acute ischemic stroke
intravenous thrombolysis
hemorrhagic transformation
machine learning
explainability
Acesso em linha:https://www.frontiersin.org/articles/10.3389/fneur.2024.1446250/full
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