Machine learning to predict in-stent stenosis after Pipeline embolization device placement

BACKGROUND: The Pipeline embolization device (PED) is a flow diverter used to treat intracranial aneurysms. In-stent stenosis (ISS) is a common complication of PED placement that can affect long-term outcome. This study aimed to establish a feasible, effective, and reliable model to predict ISS usin...

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Detalles Bibliográficos
Autores principales: Wei, Dachao, Deng, Dingwei, Gui, Siming, You, Wei, Feng, Junqiang, Meng, Xiangyu, Chen, Xiheng, Lv, Jian, Tang, Yudi, Chen, Ting, Liu, Peng
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/PMC9486156/
https://www.ncbi.nlm.nih.gov/pubmed/36147044
http://dx.doi.org/10.3389/fneur.2022.912984

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9486156/
https://www.ncbi.nlm.nih.gov/pubmed/36147044
http://dx.doi.org/10.3389/fneur.2022.912984

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