Machine learning for predicting functional outcomes in acute ischemic stroke: insights from a nationwide stroke registry

Abstract Accurately predicting the prognosis of patients with acute ischemic stroke at discharge remains highly challenging after active treatment. The aim of this retrospective nationwide registry-based study was to identify key predictors associated with favorable outcomes and to develop machine l...

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Detalhes bibliográficos

Principais autores:	Taehoon Ko, Kanghyuk Lee, Yong Uk Kwon, Yu Ra Lee, So Young Han, Jae Sang Oh
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Nature Portfolio 2026-01-01
coleção:	Scientific Reports
Assuntos:	Acute ischemic stroke Functional outcomes Stroke registry Machine learning Predictive modeling Random forest
Acesso em linha:	https://doi.org/10.1038/s41598-026-37159-w
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