Post-COVID-19 interstitial lung disease: Insights from a machine learning radiographic model
- 1Department of Respiratory Medicine, University General Hospital of Patras, Patras, Greece
- 2Department of Infectious Diseases-COVID-19 Unit, Laiko General Hospital, Athens, Greece
- 3Department of Respiratory Medicine, Corfu General Hospital, Corfu, Greece
- 4Laboratory of Molecular and Cellular Pneumonology, Department of Thoracic Medicine, Medical School, University of Crete, Heraklion, Greece
- 55th Department of Respiratory Medicine, Hospital for Thoracic Diseases, ‘SOTIRIA', Athens, Greece
- 6Medical School, National and Kapodistrian University of Athens, Zografou, Greece
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.
Funding
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.
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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, atzouvelekis@upatras.gr; argyris.tzouvelekis@gmail.com
†These authors have contributed equally to this work and share first authorship