CORRECTION article

Front. Cardiovasc. Med., 09 December 2022

Sec. Cardiac Rhythmology

Volume 9 - 2022 | https://doi.org/10.3389/fcvm.2022.1078223

Corrigendum: Artificial intelligence-assisted remote detection of ST-elevation myocardial infarction using a mini-12-lead electrocardiogram device in prehospital ambulance care

  • 1. Division of Cardiovascular Medicine, Department of Medicine, China Medical University Hospital, Taichung, Taiwan

  • 2. Graduate Institute of Biomedical Sciences, China Medical University, Taichung, Taiwan

  • 3. Division of Cardiovascular Medicine, Asia University Hospital, Taichung, Taiwan

  • 4. Department of Medical Laboratory Science and Biotechnology, Asia University, Taichung, Taiwan

  • 5. AI Center for Medical Diagnosis, China Medical University Hospital, Taichung, Taiwan

  • 6. School of Post-Baccalaureate Chinese Medicine, China Medical University, Taichung, Taiwan

  • 7. Department of Chinese Medicine, China Medical University Hospital, Taichung, Taiwan

  • 8. Ever Fortune AI Co., Ltd., Taichung, Taiwan

  • 9. School of Medicine, China Medical University, Taichung, Taiwan

  • 10. Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan

  • 11. Center of Institutional Research and Development, Asia University, Taichung, Taiwan

In the original article, there was an error in Figure 1: “The flowchart of the AI-based pre-hospital STEMI detection system” as published. A typo error in the figure read “Prehospital 12-lead ECG examinectin,” and has been corrected to “Prehospital 12-lead ECG examination.” The corrected figure appears below.

Figure 1

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.

Statements

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.

Summary

Keywords

artificial intelligence (AI), contact-to-balloon (C2B) time, convolutional neural network and long short-term memory (CNN-LSTM), prehospital 12-lead ECGs, ST-elevation myocardial infarction (STEMI)

Citation

Chen K-W, Wang Y-C, Liu M-H, Tsai B-Y, Wu M-Y, Hsieh P-H, Wei J-T, Shih ESC, Shiao Y-T, Hwang M-J, Wu Y-L, Hsu K-C and Chang K-C (2022) Corrigendum: Artificial intelligence-assisted remote detection of ST-elevation myocardial infarction using a mini-12-lead electrocardiogram device in prehospital ambulance care. Front. Cardiovasc. Med. 9:1078223. doi: 10.3389/fcvm.2022.1078223

Received

24 October 2022

Accepted

24 November 2022

Published

09 December 2022

Volume

9 - 2022

Edited and reviewed by

Roohallah Alizadehsani, Deakin University, Australia

Updates

Copyright

*Correspondence: Kuan-Cheng Chang

†These authors have contributed equally to this work

This article was submitted to Cardiac Rhythmology, 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.

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