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CORRECTION article

Front. Med., 12 November 2024
Sec. Hepatobiliary Diseases

Corrigendum: Deep learning-driven ultrasound-assisted diagnosis: optimizing GallScopeNet for precise identification of biliary atresia

  • 1College of Information Engineering, Sichuan Agricultural University, Ya'an, China
  • 2Artificial Intelligence Laboratory, Sichuan Agricultural University, Ya'an, China
  • 3College of Veterinary Medicine, Sichuan Agricultural University, Chengdu, China
  • 4Ya'an People's Hospital, Ya'an, Sichuan, China
  • 5Department of Neurology, The Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan, China

A Corrigendum on
Deep learning-driven ultrasound-assisted diagnosis: optimizing GallScopeNet for precise identification of biliary atresia

by Niu, Y., Li, J., Xu, X., Luo, P., Liu, P., Wang, J., and Mu, J. (2024). Front. Med. 11:1445069. doi: 10.3389/fmed.2024.1445069

In the published article, there was an error regarding the affiliations for Pingchuan Liu and Jian Wang. As well as having affiliation 4, they should also have “Department of Neurology, The Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan, China”.

In the published article, there was an error in the Funding statement. The funding statement originally only included “the Health Commission of Sichuan Province, project number 23LCYJ034” and omitted additional funding sources. The correct Funding statement appears below.

Funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This study was funded by Central Government Guides Local Scientific and Technological Development Project (Grant No. 2022ZYD0097), Sichuan Provincial Health Commission Special Clinical Research Project (Grant No. 23LCYJ034), Sichuan Medical Youth Innovation Research Project (Grant No. Q21049), Sichuan Medical Science and Technology Innovation Research Association Project (Grant No. YCH-KY-YCZD2024-037), and the Health Commission of Sichuan Province, project number 23LCYJ034.

The authors apologize for these errors 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: biliary atresia (BA), deep learning, ultrasound diagnosis, feature extraction, clinical application

Citation: Niu Y, Li J, Xu X, Luo P, Liu P, Wang J and Mu J (2024) Corrigendum: Deep learning-driven ultrasound-assisted diagnosis: optimizing GallScopeNet for precise identification of biliary atresia. Front. Med. 11:1518391. doi: 10.3389/fmed.2024.1518391

Received: 28 October 2024; Accepted: 29 October 2024;
Published: 12 November 2024.

Approved by:

Frontiers Editorial Office, Frontiers Media SA, Switzerland

Copyright © 2024 Niu, Li, Xu, Luo, Liu, Wang and Mu. 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: Jiong Mu, am11JiN4MDAwNDA7c2ljYXUuZWR1LmNu; Jian Wang, NDAzNzkxNjU5JiN4MDAwNDA7cXEuY29t

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.