![Man ultramarathon runner in the mountains he trains at sunset](https://d2csxpduxe849s.cloudfront.net/media/E32629C6-9347-4F84-81FEAEF7BFA342B3/0B4B1380-42EB-4FD5-9D7E2DBC603E79F8/webimage-C4875379-1478-416F-B03DF68FE3D8DBB5.png)
94% of researchers rate our articles as excellent or good
Learn more about the work of our research integrity team to safeguard the quality of each article we publish.
Find out more
ERRATUM article
Front. Cardiovasc. Med. , 14 March 2024
Sec. Cardiac Rhythmology
Volume 11 - 2024 | https://doi.org/10.3389/fcvm.2024.1396396
This article is part of the Research Topic Artificial Intelligence in Cardiac Rhythmology View all 8 articles
This article is an erratum on:
Convolutional neural network (CNN)-enabled electrocardiogram (ECG) analysis: a comparison between standard twelve-lead and single-lead setups
An Erratum on:
By Saglietto A, Baccega D, Esposito R, Anselmino M, Dusi V, Fiandrotti A and De Ferrari GM (2024). Front. Cardiovasc. Med. 11:1327179. doi: 10.3389/fcvm.2024.1327179
Due to a production error, the first sentence of the Results paragraph in the abstract was incorrectly given as “The CNN based on single-lead ECG (D1) outperformed the one based on the standard 12-lead framework [with an average percentage difference of the area under the curve (AUC) of −8.7%].”.
This has been corrected to “The CNN based on single-lead ECG (D1) achieved satisfactory performance compared to the standard 12-lead framework (average percentage AUC difference: −8.7%).”
The publisher apologizes for this mistake. The original version of this article has been updated.
Keywords: artificial intelligence, deep learning, electrocardiogram, single-lead, screening
Citation: Frontiers Production Office (2024) Erratum: Convolutional neural network (CNN)-enabled electrocardiogram (ECG) analysis: a comparison between standard twelve-lead and single-lead setups. Front. Cardiovasc. Med. 11:1396396. doi: 10.3389/fcvm.2024.1396396
Received: 5 March 2024; Accepted: 5 March 2024;
Published: 14 March 2024.
Approved by: Frontiers Editorial Office, Frontiers Media SA, Switzerland
© 2024 Frontiers Production Office. 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: Frontiers Production Office cHJvZHVjdGlvbi5vZmZpY2VAZnJvbnRpZXJzaW4ub3Jn
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.
Research integrity at Frontiers
Learn more about the work of our research integrity team to safeguard the quality of each article we publish.