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
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中图分类号
学科分类号
摘要
引用
收藏
页码:5841 / 5851
页数:10
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