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CORRECTION article

Front. Cardiovasc. Med., 24 March 2022
Sec. Cardiovascular Surgery
This article is part of the Research Topic Translating Artificial Intelligence into Clinical Use within Cardiology View all 19 articles

Corrigendum: Machine Learning for the Prediction of Complications in Patients After Mitral Valve Surgery

\nHaiye Jiang,&#x;Haiye Jiang1,2Leping Liu&#x;Leping Liu3Yongjun WangYongjun Wang4Hongwen JiHongwen Ji5Xianjun MaXianjun Ma6Jingyi WuJingyi Wu7Yuanshuai HuangYuanshuai Huang8Xinhua WangXinhua Wang9Rong Gui
Rong Gui3*Qinyu Zhao
Qinyu Zhao10*Bingyu Chen
Bingyu Chen11*
  • 1Clinical Laboratory, The Third Xiangya Hospital, Central South University, Changsha, China
  • 2Hunan Engineering Technology Research Center of Optoelectronic Health Detection, Changsha, China
  • 3Department of Transfusion, The Third Xiangya Hospital, Central South University, Changsha, China
  • 4Department of Blood Transfusion, The Second Xiangya Hospital, Central South University, Changsha, China
  • 5Department of Anesthesiology, Fuwai Hospital National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
  • 6Department of Blood Transfusion, Qilu Hospital of Shandong University, Jinan, China
  • 7Department of Transfusion, Xiamen Cardiovascular Hospital Xiamen University, Xiamen, China
  • 8Department of Transfusion, The Affiliated Hospital of Southwest Medical University, Luzhou, China
  • 9Department of Transfusion, Beijing Aerospace General Hospital, Beijing, China
  • 10College of Engineering & Computer Science, Australian National University, Canberra, ACT, Australia
  • 11Department of Transfusion, Zhejiang Provincial People's Hospital, Hangzhou, China

A Corrigendum on
Machine Learning for the Prediction of Complications in Patients After Mitral Valve Surgery

by Jiang, H., Liu, L., Wang, Y., Ji, H., Ma, X., Wu, J., Huang, Y., Wang, X., Gui, R., Zhao, Q., and Chen, B., (2021). Front. Cardiovasc. Med. 8:771246. doi: 10.3389/fcvm.2021.771246

In the published article, there were two errors in the affiliations. The first error is that “Haiye Jiang1†” should have a new affiliation 2 “Hunan Engineering Technology Research Center of Optoelectronic Health Detection, Changsha, Hunan, China,” and change it to “Haiye Jiang1, 2†”. The second error is “Qinyu Zhao2, 9*” should have affiliation 2 removed “Department of Transfusion, The Third Xiangya Hospital, Central South University, Changsha, Hunan, China,” and change it to “ Qinyu Zhao10*”.

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.

Publisher's Note

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.

Keywords: machine learning, cardiac valvular surgery, complications, predict, model

Citation: Jiang H, Liu L, Wang Y, Ji H, Ma X, Wu J, Huang Y, Wang X, Gui R, Zhao Q and Chen B (2022) Corrigendum: Machine Learning for the Prediction of Complications in Patients After Mitral Valve Surgery. Front. Cardiovasc. Med. 9:890752. doi: 10.3389/fcvm.2022.890752

Received: 06 March 2022; Accepted: 07 March 2022;
Published: 24 March 2022.

Approved by:

Frontiers Editorial Office, Frontiers Media SA, Switzerland

Copyright © 2022 Jiang, Liu, Wang, Ji, Ma, Wu, Huang, Wang, Gui, Zhao and Chen. 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: Rong Gui, YWd1aXJvbmcmI3gwMDA0MDsxNjMuY29t; Bingyu Chen, MTg0NDAzNTg4MCYjeDAwMDQwO3FxLmNvbQ==; Qinyu Zhao, cWlueXUuemhhbyYjeDAwMDQwO2FudS5lZHUuYXU=

These authors have contributed equally to this work

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.