CORRECTION article

Front. Cardiovasc. Med., 08 February 2022

Sec. Cardiovascular Surgery

Volume 9 - 2022 | https://doi.org/10.3389/fcvm.2022.854588

This article is part of the Research TopicTranslating Artificial Intelligence into Clinical Use within CardiologyView all 19 articles

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

A correction has been applied to this article in:

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

    1. Read correction
Haiye Jiang&#x;Haiye Jiang1†Leping Liu&#x;Leping Liu2†Yongjun WangYongjun Wang3Hongwen JiHongwen Ji4Xianjun MaXianjun Ma5Jingyi WuJingyi Wu6Yuanshuai HuangYuanshuai Huang7Xinhua WangXinhua Wang8Rong Gui Rong Gui2*Qinyu Zhao, Qinyu Zhao2,9*Bingyu Chen Bingyu Chen10*
  • 1Clinical Laboratory, The Third Xiangya Hospital, Central South University, Changsha, China
  • 2Department of Transfusion, The Third Xiangya Hospital, Central South University, Changsha, China
  • 3Department of Blood Transfusion, The Second Xiangya Hospital, Central South University, Changsha, China
  • 4Department of Anesthesiology, Fuwai Hospital National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
  • 5Department of Blood Transfusion, Qilu Hospital of Shandong University, Jinan, China
  • 6Department of Transfusion, Xiamen Cardiovascular Hospital Xiamen University, Xiamen, China
  • 7Department of Transfusion, The Affiliated Hospital of Southwest Medical University, Luzhou, China
  • 8Department of Transfusion, Beijing Aerospace General Hospital, Beijing, China
  • 9College of Engineering & Computer Science, Australian National University, Canberra, ACT, Australia
  • 10Department 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 was an error in affiliation for authors Xinhua Wang and Rong Gui. Instead of “Xinhua Wang7, Rong Gui8*”, it should be “Xinhua Wang8, Rong Gui2*”.

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. 9:854588. doi: 10.3389/fcvm.2022.854588

Received: 14 January 2022; Accepted: 17 January 2022;
Published: 08 February 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, YWd1aXJvbmdAMTYzLmNvbQ==; Bingyu Chen, MTg0NDAzNTg4MEBxcS5jb20=; Qinyu Zhao, cWlueXUuemhhb0BhbnUuZWR1LmF1

†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.