Deep learning and machine learning predictive models for neurological function after interventional embolization of intracranial aneurysms

Deep learning and machine learning predictive models for neurological function after interventional embolization of intracranial aneurysms

ObjectiveThe objective of this study is to develop a model to predicts the postoperative Hunt-Hess grade in patients with intracranial aneurysms by integrating radiomics and deep learning technologies, using preoperative CTA imaging data. Thereby assisting clinical decision-making and improving the...

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Bibliographic Details
Main Authors: Yan Peng, Yiren Wang, Zhongjian Wen, Hongli Xiang, Ling Guo, Lei Su, Yongcheng He, Haowen Pang, Ping Zhou, Xiang Zhan
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-01-01
Series:Frontiers in Neurology
Subjects:
radiomics
deep learning
machine learning
prediction model
artificial intelligence
Online Access:https://www.frontiersin.org/articles/10.3389/fneur.2024.1321923/full

Internet

https://www.frontiersin.org/articles/10.3389/fneur.2024.1321923/full

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