The journal retracts the 10 August 2021 article cited above.
Following publication, the publisher uncovered evidence that false identities were used in the peer-review process. The assignment of fake reviewers was confirmed by an investigation, conducted in accordance with Frontiers' policies and the Committee on Publication Ethics (COPE) guidelines. Given the concerns, the editors no longer have confidence in the findings presented in the article. UPDATE (30 July 2024): This notice is to alert readers of this matter, it does not imply involvement of the co-authors.
This retraction was approved by the Chief Editors of Frontiers in Public Health and the Chief Executive Editor of Frontiers. The authors received a communication regarding the retraction and had a chance to respond. This communication has been recorded by the publisher.
Summary
Keywords
Convolutional Neural Network, fractional max pooling, Data augmentation, COVID-19, Average pooling, Model averaging
Citation
Frontiers Editorial Office (2024) Retraction: Deep fractional max pooling neural network for COVID-19 recognition. Front. Public Health 11:1358295. doi: 10.3389/fpubh.2023.1358295
Received
19 December 2023
Accepted
21 December 2023
Published
03 January 2024
Approved by
Paolo Vineis, Imperial College London, United Kingdom
Volume
11 - 2023
Updates
Copyright
© 2024 Frontiers Editorial 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 Editorial Office research.integrity@frontiersin.org
Disclaimer
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