Personalized risk prediction of symptomatic intracerebral hemorrhage after stroke thrombolysis using a machine-learning model

BACKGROUND: Personalized prediction of the risk of symptomatic intracerebral hemorrhage (sICH) after stroke thrombolysis is clinically useful. Machine-learning-based modeling may provide the personalized prediction of the risk of sICH after stroke thrombolysis. METHODS: We identified 2578 thrombolys...

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Detalles Bibliográficos
Autores principales: Wang, Feng, Huang, Yuanhanqing, Xia, Yong, Zhang, Wei, Fang, Kun, Zhou, Xiaoyu, Yu, Xiaofei, Cheng, Xin, Li, Gang, Wang, Xiaoping, Luo, Guojun, Wu, Danhong, Liu, Xueyuan, Campbell, Bruce C.V., Dong, Qiang, Zhao, Yuwu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2020
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8842114/
https://www.ncbi.nlm.nih.gov/pubmed/35173804
http://dx.doi.org/10.1177/1756286420902358

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8842114/
https://www.ncbi.nlm.nih.gov/pubmed/35173804
http://dx.doi.org/10.1177/1756286420902358

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