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Updated: Jul 27, 2025

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基于机器学习的识别症状性大脑动脉样硬化斑块与双能量计算机断层扫描血管学

Ling-Jie Wang1, Pei-Qing Zhai1, Li-Li Xue1

  • 1Department of Radiology, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province 030001, PR China.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
|June 8, 2023
PubMed
概括

机器学习模型使用双能CT (DECT) 血管图像特征,如脂肪分数 (FF),可以识别症状性动脉斑块. 这种方法通过提供非侵入性诊断工具,有助于预防脑血管事件.

关键词:
冠状动脉斑块的形成双能量计算机断层扫描血管图谱.缺血性中风 缺血性中风机器学习 机器学习过渡性缺血性心脏病发作是短暂的

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