In the original article, we neglected to include the funder “National Key Research and Development Program of China (2019YFE0107800), Beijing Municipal Science and Technology Commission (Z201100005620009) to ZY, and National Research Foundation of Korea (2019K1A3A1A20093097) to MH.”
The correct funding statement appears below:
“This study received funding from National Key Research and Development Program of China (2019YFE0107800), Beijing Municipal Science and Technology Commission (Z201100005620009) to ZY, and National Research Foundation of Korea (2019K1A3A1A20093097) to MH. The funders had the following involvement with the study. All the funders provided financial support for patient enrollment, data collection, database construction, and management.”
The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.
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Summary
Keywords
coronary artery disease, computed tomographic angiography, deep learning, invasive coronary angiography (ICA), diagnostic test
Citation
Xu L, He Y, Luo N, Guo N, Hong M, Jia X, Wang Z and Yang Z (2022) Corrigendum: Diagnostic Accuracy and Generalizability of a Deep Learning-Based Fully Automated Algorithm for Coronary Artery Stenosis Detection on CCTA: A Multi-Centre Registry Study. Front. Cardiovasc. Med. 9:920738. doi: 10.3389/fcvm.2022.920738
Received
15 April 2022
Accepted
24 May 2022
Published
13 June 2022
Approved by
Frontiers Editorial Office, Frontiers Media SA, Switzerland
Volume
9 - 2022
Updates
Copyright
© 2022 Xu, He, Luo, Guo, Hong, Jia, Wang and Yang.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Zhenghan Yang yangzhenghan@vip.163.comZhenchang Wang cjr.wzhch@vip.163.com
†These authors have contributed equally to this work
This article was submitted to Cardiovascular Imaging, a section of the journal Frontiers in Cardiovascular Medicine
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.