Machine learning-based prediction of symptomatic intracerebral hemorrhage after intravenous thrombolysis for stroke: a large multicenter study

BACKGROUND: This study aimed to compare the performance of different machine learning models in predicting symptomatic intracranial hemorrhage (sICH) after thrombolysis treatment for ischemic stroke. METHODS: This multicenter study utilized the Shenyang Stroke Emergency Map database, comprising 8,92...

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Detalles Bibliográficos
Autores principales: Wen, Rui, Wang, Miaoran, Bian, Wei, Zhu, Haoyue, Xiao, Ying, He, Qian, Wang, Yu, Liu, Xiaoqing, Shi, Yangdi, Hong, Zhe, Xu, Bing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Neurology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10624225/
https://www.ncbi.nlm.nih.gov/pubmed/37928151
http://dx.doi.org/10.3389/fneur.2023.1247492

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10624225/
https://www.ncbi.nlm.nih.gov/pubmed/37928151
http://dx.doi.org/10.3389/fneur.2023.1247492

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