In the published article, there was an error in the Funding statement. The Funding statement is incomplete. The correct Funding statement appears below.
Statements
Funding
This work was supported by Qinghai Province Basic Research Plan—Applied Basic Research Project (2020-ZJ-781).
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.
Summary
Keywords
lung nodules, artificial intelligence, multimodal, malignancy, attention mechanism gate module
Citation
Liu G, Liu F, Gu J, Mao X, Xie X and Sang J (2024) Corrigendum: An attention-based deep learning network for lung nodule malignancy discrimination. Front. Neurosci. 17:1357511. doi: 10.3389/fnins.2023.1357511
Received
18 December 2023
Accepted
22 December 2023
Published
12 January 2024
Approved by
Frontiers Editorial Office, Frontiers Media SA, Switzerland
Volume
17 - 2023
Updates
Copyright
© 2024 Liu, Liu, Gu, Mao, Xie and Sang.
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: Gang Liu liu_gang197508@163.com
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.