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Articles Published Processes
7/9/2021 8:50:00 AM | Browse: 501 | Download: 1055
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Received |
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2021-05-22 02:27 |
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Peer-Review Started |
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2021-05-22 02:30 |
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To Make the First Decision |
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Return for Revision |
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2021-06-16 01:20 |
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Revised |
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2021-06-20 18:19 |
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Second Decision |
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2021-07-02 06:49 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2021-07-02 11:46 |
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Articles in Press |
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2021-07-02 11:46 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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2021-07-07 02:42 |
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Typeset the Manuscript |
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2021-07-09 05:22 |
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Publish the Manuscript Online |
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2021-07-09 08:50 |
ISSN |
2644-3260 (online) |
Open Access |
This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ |
Copyright |
© The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved. |
Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
Website |
http://www.wjgnet.com |
Category |
Medical Laboratory Technology |
Manuscript Type |
Minireviews |
Article Title |
Artificial intelligence in coronary computed tomography angiography imaging
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Manuscript Source |
Invited Manuscript |
All Author List |
Zhe-Zhe Zhang, Yan Guo and Yang Hou |
ORCID |
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Funding Agency and Grant Number |
Funding Agency |
Grant Number |
National Natural Science Foundation of China |
82071920 |
Key Research & Development Plan of Liaoning Province |
2020JH2/10300037 |
National Natural Science Foundation of China |
81901741 |
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Corresponding Author |
Yang Hou, PhD, Professor, Department of Radiology, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Heping District, Shenyang 110004, Liaoning Province, China. houyang1973@163.com |
Key Words |
Coronary computed tomography angiography; Coronary artery disease; Artificial intelligence; Deep learning; Machine learning; Prognosis |
Core Tip |
The application of artificial intelligence in coronary computed tomography angiography images mainly focused on the following aspects: (1) Studies based on the coronary arteries and plaques for determination of stenosis degree, identification of plaque types, quantification of coronary artery calcium score, prediction of myocardial infarction, and prognosis; (2) Studies around the perivascular adipose tissue, which was mainly conducted using radiomics analysis and machine learning algorithm, for improvement of risk stratification; (3) Studies based on the texture analysis of the left ventricular myocardium for assessment of functionally significant stenosis or for prognosis. |
Publish Date |
2021-07-09 08:50 |
Citation |
Zhang ZZ, Guo Y, Hou Y. Artificial intelligence in coronary computed tomography angiography imaging. Artif Intell Med Imaging 2021; 2(3): 73-85 |
URL |
https://www.wjgnet.com/2644-3260/full/v2/i3/73.htm |
DOI |
https://dx.doi.org/10.35711/aimi.v2.i3.73 |
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