Predicting futile recanalization, malignant cerebral edema, and cerebral herniation using intelligible ensemble machine learning following mechanical thrombectomy for acute ischemic stroke

PURPOSE: To establish an ensemble machine learning (ML) model for predicting the risk of futile recanalization, malignant cerebral edema (MCE), and cerebral herniation (CH) in patients with acute ischemic stroke (AIS) who underwent mechanical thrombectomy (MT) and recanalization. METHODS: This prosp...

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Detalles Bibliográficos
Autores principales: Zeng, Weixiong, Li, Wei, Huang, Kaibin, Lin, Zhenzhou, Dai, Hui, He, Zilong, Liu, Renyi, Zeng, Zhaodong, Qin, Genggeng, Chen, Weiguo, Wu, Yongming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Neurology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9554641/
https://www.ncbi.nlm.nih.gov/pubmed/36247767
http://dx.doi.org/10.3389/fneur.2022.982783

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9554641/
https://www.ncbi.nlm.nih.gov/pubmed/36247767
http://dx.doi.org/10.3389/fneur.2022.982783

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