Machine Learning?Based Prediction of Small Intracranial Aneurysm Rupture Status Using CTA-Derived Hemodynamics: A Multicenter Study
Machine Learning?Based Prediction of Small Intracranial Aneurysm Rupture Status Using CTA-Derived Hemodynamics: A Multicenter Study
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DOI：
10.3174/ajnr.a7034
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发表时间：
2021-04-01
影响因子：
3.5
通讯作者：
Zhang, L. J.
中科院分区：
文献类型：
--
作者：
Shi, Z.;Chen, G. Z.;Zhang, L. J.
背景与目的：颅内小动脉瘤越来越多地被发现，但其破裂风险尚不清楚。我们的目标是通过结合临床、形态学和基于机器学习技术的血流动力学信息来开发小动脉瘤的破裂风险模型，并在外部验证数据集中对模型进行测试。材料与方法：2010年1月至2016年12月，连续400例只有小动脉瘤的患者(
BACKGROUND AND PURPOSE:Small intracranial aneurysms are being increasingly detected while the rupture risk is not well-understood. We aimed to develop rupture-risk models of small aneurysms by combining clinical, morphologic, and hemodynamic information based on machine learning techniques and to test the models in external validation datasets.MATERIALS AND METHODS:From January 2010 to December 2016, five hundred four consecutive patients with only small aneurysms (