Skip to main content

CORRECTION article

Front. Oncol., 18 October 2021
Sec. Cancer Imaging and Image-directed Interventions
Volume 11 - 2021 | https://doi.org/10.3389/fonc.2021.774369

Corrigendum: Machine Learning-Based Analysis of Magnetic Resonance Radiomics for the Classification of Gliosarcoma and Glioblastoma

This article is a correction to:

  1. Machine Learning-Based Analysis of Magnetic Resonance Radiomics for the Classification of Gliosarcoma and Glioblastoma

    1. Read original article
Zenghui Qian&#x;Zenghui Qian1†Lingling Zhang&#x;Lingling Zhang2†Jie HuJie Hu1Shuguang ChenShuguang Chen3Hongyan ChenHongyan Chen2Huicong ShenHuicong Shen2Fei ZhengFei Zheng2Yuying ZangYuying Zang2Xuzhu Chen*Xuzhu Chen2*
  • 1Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
  • 2Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
  • 3School of Mathematical Sciences, Nankai University, Tianjin, China

A Corrigendum on
Machine Learning-Based Analysis of Magnetic Resonance Radiomics for the Classification of Gliosarcoma and Glioblastoma

By Qian Z, Zhang L, Hu J, Chen S, Chen H, Shen H, Zheng F, Zang Y and Chen X (2021). Front. Oncol. 11:699789. doi: 10.3389/fonc.2021.699789

In the published article, there was a mistake in the order of authors. The co-first author was incorrectly written as the second author. The correct author list with the correct author order appears below.

“Zenghui Qian1†, Lingling Zhang2†, Jie Hu1, Shuguang Chen3, Hongyan Chen2, Huicong Shen2, Fei Zheng2, Yuying Zang2, Xuzhu Chen2*”

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: gliosarcoma, glioblastoma, machine learning, radiomics, differentiation

Citation: Qian Z, Zhang L, Hu J, Chen S, Chen H, Shen H, Zheng F, Zang Y and Chen X (2021) Corrigendum: Machine Learning-Based Analysis of Magnetic Resonance Radiomics for the Classification of Gliosarcoma and Glioblastoma. Front. Oncol. 11:774369. doi: 10.3389/fonc.2021.774369

Received: 11 September 2021; Accepted: 04 October 2021;
Published: 18 October 2021.

Approved by:

Frontiers Editorial Office, Frontiers Media SA, Switzerland

Copyright © 2021 Qian, Zhang, Hu, Chen, Chen, Shen, Zheng, Zang and Chen. 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: Xuzhu Chen, radiology888@aliyun.com

†These authors share first authorship

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.