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CORRECTION article
Front. Med. , 13 April 2023
Sec. Pulmonary Medicine
Volume 10 - 2023 | https://doi.org/10.3389/fmed.2023.1194925
This article is part of the Research Topic Immune-Mediated Lung Injury View all 15 articles
This article is a correction to:
Post-COVID-19 interstitial lung disease: Insights from a machine learning radiographic model
A corrigendum on
Post-COVID-19 interstitial lung disease: Insights from a machine learning radiographic model
by Karampitsakos, T., Sotiropoulou, V., Katsaras, M., Tsiri, P., Georgakopoulou, V. E., Papanikolaou, I. C., Bibaki, E., Tomos, I., Lambiri, I., Papaioannou, O., Zarkadi, E., Antonakis, E., Pandi, A., Malakounidou, E., Sampsonas, F., Makrodimitri, S., Chrysikos, S., Hillas, G., Dimakou, K., Tzanakis, N., Sipsas, N. V., Antoniou, K., and Tzouvelekis, A. (2023). Front. Med. 9:1083264. doi: 10.3389/fmed.2022.1083264
In the published article, the Funding statement was not reported. The correct Funding statement appears below.
The publication fees of this manuscript have been financed by the Research Council of the University of Patras.
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.
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: post-COVID-19, long COVID, interstitial lung disease, antifibrotics, machine learning
Citation: Karampitsakos T, Sotiropoulou V, Katsaras M, Tsiri P, Georgakopoulou VE, Papanikolaou IC, Bibaki E, Tomos I, Lambiri I, Papaioannou O, Zarkadi E, Antonakis E, Pandi A, Malakounidou E, Sampsonas F, Makrodimitri S, Chrysikos S, Hillas G, Dimakou K, Tzanakis N, Sipsas NV, Antoniou K and Tzouvelekis A (2023) Corrigendum: Post-COVID-19 interstitial lung disease: Insights from a machine learning radiographic model. Front. Med. 10:1194925. doi: 10.3389/fmed.2023.1194925
Received: 27 March 2023; Accepted: 28 March 2023;
Published: 13 April 2023.
Approved by:
Frontiers Editorial Office, Frontiers Media SA, SwitzerlandCopyright © 2023 Karampitsakos, Sotiropoulou, Katsaras, Tsiri, Georgakopoulou, Papanikolaou, Bibaki, Tomos, Lambiri, Papaioannou, Zarkadi, Antonakis, Pandi, Malakounidou, Sampsonas, Makrodimitri, Chrysikos, Hillas, Dimakou, Tzanakis, Sipsas, Antoniou and Tzouvelekis. 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: Argyris Tzouvelekis, YXR6b3V2ZWxla2lzQHVwYXRyYXMuZ3I=; YXJneXJpcy50em91dmVsZWtpc0BnbWFpbC5jb20=
†These authors have contributed equally to this work and share first authorship
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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