Impact of machine learning–based coronary computed tomography angiography fractional flow reserve on treatment decisions and clinical outcomes in patients with suspected coronary artery disease

被引：0
作者：
Hong Yan Qiao
Chun Xiang Tang
U. Joseph Schoepf
Christian Tesche
Richard R. Bayer
Dante A Giovagnoli
H. Todd Hudson
Chang Sheng Zhou
Jing Yan
Meng Jie Lu
Fan Zhou
Guang Ming Lu
Jian Wei Jiang
Long Jiang Zhang
机构：
[1] Nanjing Medical University,Department of Medical Imaging, Jinling Hospital
[2] Affiliated Hospital of Jiangnan University,Department of Medical Imaging
[3] Medical School of Nanjing University,Department of Medical Imaging, Jinling Hospital
[4] Medical University of South Carolina,Division of Cardiovascular Imaging, Department of Radiology and Radiological Science
[5] Heart Center Munich-Bogenhausen,Department of Cardiology and Intensive Care Medicine
[6] Ludwig-Maximilians-University,Department of Cardiology, Munich University Clinic
[7] Siemens Healthcare Ltd.,undefined
来源：
European Radiology | 2020年 / 30卷
关键词：
Coronary artery disease; Computed tomography angiography; Machine learning; Myocardial fractional flow reserve;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
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页码：5841 / 5851
页数：10
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