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基于机器学习的缺血特异性狭窄性预测:一项中国多中心冠状动脉CT血管学研究

Xiao Lei Zhang1, Bo Zhang2, Chun Xiang Tang1

  • 1Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu 210002, PR China.

European journal of radiology
|October 12, 2023
PubMed
概括

使用冠状动脉计算机断层扫描血管学 (CCTA) 数据的机器学习算法可以有效地预测病变特异性缺血. 结合CCTA特征和CT衍生的分流储备 (CT-FFR) 的多参数模型显示出卓越的诊断性能.

关键词:
冠状动脉CT血管造影 (CT) 是一种冠状动脉CT血管造影.决策树是一个决策树.分量流量储备部分流量储备缺血 缺血是因为缺血.机器学习是机器学习.

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