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CORRECTION article

Front. Med., 05 June 2025

Sec. Dermatology

Volume 12 - 2025 | https://doi.org/10.3389/fmed.2025.1617441

Corrigendum: Advancement and independent validation of a deep learning-based tool for automated scoring of nail psoriasis severity using the modified nail psoriasis severity index


Stephan Kemenes,Stephan Kemenes1,2Liu ChangLiu Chang3Maja SchlerethMaja Schlereth4Rita Noversa de Sousa,Rita Noversa de Sousa2,5Ioanna MinopoulouIoanna Minopoulou6Pauline Fenzl,Pauline Fenzl2,5Giulia Corte,Giulia Corte2,5Melek Yalcin Mutlu,Melek Yalcin Mutlu2,5Michael Wolfgang Hner,Michael Wolfgang Höner1,2Ioannis Sagonas,Ioannis Sagonas1,2Birte Coppers,Birte Coppers2,5Anna-Maria Liphardt,Anna-Maria Liphardt2,5David SimonDavid Simon6Arnd KleyerArnd Kleyer6Lukas FolleLukas Folle3Michael Sticherling,Michael Sticherling1,2Georg Schett,Georg Schett2,5Andreas MaierAndreas Maier3Filippo Fagni,
Filippo Fagni2,5*
  • 1Department of Dermatology, Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany
  • 2Deutsches Zentrum Immuntherapie (DZI), Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany
  • 3Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
  • 4Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
  • 5Department of Internal Medicine 3 – Rheumatology and Immunology, Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, Germany
  • 6Department of Rheumatology and Clinical Immunology, Charité – Universitätsmedizin Berlin, Berlin, Germany

A Corrigendum on
Advancement and independent validation of a deep learning-based tool for automated scoring of nail psoriasis severity using the modified nail psoriasis severity index

by Kemenes, S., Chang, L., Schlereth, M., Noversa de Sousa, R., Minopoulou, I., Fenzl, P., Corte, G., Yalcin Mutlu, M., Höner, M. W., Sagonas, I., Coppers, B., Liphardt, A.-M., Simon, D., Kleyer, A., Folle, L., Sticherling, M., Schett, G., Maier, A., and Fagni, F. (2025). Front. Med. 12:1574413. doi: 10.3389/fmed.2025.1574413

In the published article, an author name was incorrectly written as Anna-Maria Liphart. The correct spelling is Anna-Maria Liphardt.

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.

Keywords: psoriasis, psoriatic arthritis, nail disease, NAPSI, MNAPSI, artificial intelligence, machine learning, outcome measures

Citation: Kemenes S, Chang L, Schlereth M, Noversa de Sousa R, Minopoulou I, Fenzl P, Corte G, Yalcin Mutlu M, Höner MW, Sagonas I, Coppers B, Liphardt A-M, Simon D, Kleyer A, Folle L, Sticherling M, Schett G, Maier A and Fagni F (2025) Corrigendum: Advancement and independent validation of a deep learning-based tool for automated scoring of nail psoriasis severity using the modified nail psoriasis severity index. Front. Med. 12:1617441. doi: 10.3389/fmed.2025.1617441

Received: 24 April 2025; Accepted: 23 May 2025;
Published: 05 June 2025.

Approved by:

Frontiers Editorial Office, Frontiers Media SA, Switzerland

Copyright © 2025 Kemenes, Chang, Schlereth, Noversa de Sousa, Minopoulou, Fenzl, Corte, Yalcin Mutlu, Höner, Sagonas, Coppers, Liphardt, Simon, Kleyer, Folle, Sticherling, Schett, Maier and Fagni. 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: Filippo Fagni, ZmlsaXBwby5mYWduaUB1ay1lcmxhbmdlbi5kZQ==

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.