In the published article, there was an error in affiliation. Instead of “Department of Radiology, Third Hospital of Hebei Medical University, Shijiangzhuang, China”, it should be “Department of Radiology, Third Hospital of Hebei Medical University, Shijiazhuang, China”.
The original version of this article has been updated.
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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
radiomics, 2.5D deep learning, feature fusion, vertebral compression fractures, nomogram, magnetic resonance imaging
Citation
Liang W, Yu H, Duan L, Li X, Wang M, Wang B and Cui J (2025) Correction: MRI-based 2.5D deep learning radiomics nomogram for the differentiation of benign versus malignant vertebral compression fractures. Front. Oncol. 15:1632503. doi: 10.3389/fonc.2025.1632503
Received
21 May 2025
Accepted
29 May 2025
Published
11 June 2025
Approved by
Frontiers Editorial Office, Frontiers Media SA, Switzerland
Volume
15 - 2025
Updates
Copyright
© 2025 Liang, Yu, Duan, Li, Wang, Wang and Cui.
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: Jianling Cui, 36200675@hebmu.edu.cn
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.