Predicting the rupture status of small middle cerebral artery aneurysms using random forest modeling

OBJECTIVE: Small intracranial aneurysms are increasingly being detected; however, a prediction model for their rupture is rare. Random forest modeling was used to predict the rupture status of small middle cerebral artery (MCA) aneurysms with morphological features. METHODS: From January 2009 to Jun...

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Detalles Bibliográficos
Autores principales: Zhou, Jiafeng, Xia, Nengzhi, Li, Qiong, Zheng, Kuikui, Jia, Xiufen, Wang, Hao, Zhao, Bing, Liu, Jinjin, Yang, Yunjun, Chen, Yongchun
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/PMC9366079/
https://www.ncbi.nlm.nih.gov/pubmed/35968311
http://dx.doi.org/10.3389/fneur.2022.921404

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9366079/
https://www.ncbi.nlm.nih.gov/pubmed/35968311
http://dx.doi.org/10.3389/fneur.2022.921404

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