A deep learning‐based model for prediction of hemorrhagic transformation after stroke

Hemorrhagic transformation (HT) is one of the most serious complications after endovascular thrombectomy (EVT) in acute ischemic stroke (AIS) patients. The purpose of this study is to develop and validate deep‐learning (DL) models based on multiparametric magnetic resonance imaging (MRI) to automati...

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Detalles Bibliográficos
Autores principales: Jiang, Liang, Zhou, Leilei, Yong, Wei, Cui, Jinluan, Geng, Wen, Chen, Huiyou, Zou, Jianjun, Chen, Yang, Yin, Xindao, Chen, Yu‐Chen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Research Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10041160/
https://www.ncbi.nlm.nih.gov/pubmed/34608705
http://dx.doi.org/10.1111/bpa.13023

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10041160/
https://www.ncbi.nlm.nih.gov/pubmed/34608705
http://dx.doi.org/10.1111/bpa.13023

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