In the published article, there was an error in the Funding statement. The correct Funding statement appears below.
Statements
Funding
HL was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No. NRF-2022R1C1C1006237, NRF-2022R1A5A1033624, RS-2023-00227944). GC was supported by an NRF grant funded by the Korean government (No. NRF-2020R1C1C1A01012557). JP was supported by an NRF grant funded by the Korean government (No. NRF- 2021R1I1A1A01057767). YC was supported by a National Institute for Mathematical Sciences (NIMS) grant funded by the Korean government (MSIT) (No. B23820000).
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.
Summary
Keywords
COVID-19, prediction, machine learning, early detection, outbreak
Citation
Cho G, Park JR, Choi Y, Ahn H and Lee H (2024) Corrigendum: Detection of COVID-19 epidemic outbreak using machine learning. Front. Public Health 12:1381284. doi: 10.3389/fpubh.2024.1381284
Received
03 February 2024
Accepted
05 February 2024
Published
22 February 2024
Approved by
Frontiers Editorial Office, Frontiers Media SA, Switzerland
Volume
12 - 2024
Updates
Copyright
© 2024 Cho, Park, Choi, Ahn and Lee.
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: Hyojung Lee hjlee@knu.ac.kr
†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.