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Correction: A prediction model of nodal metastasis in cN0 oral squamous cell carcinoma using metabolic and pathological variables

Correction: A prediction model of nodal metastasis in cN0 oral squamous cell carcinoma using... Xu et al. Cancer Imaging (2023) 23:47 Cancer Imaging https://doi.org/10.1186/s40644-023-00563-w Open Access C ORREC TION Correction: A prediction model of nodal metastasis in cN0 oral squamous cell carcinoma using metabolic and pathological variables 1† 2† 1 1 1 3 2 1* 4* Feng Xu , Liling Peng , Junyi Feng , Xiaochun Zhu , Yifan Pan , Yuhua Hu , Xin Gao , Yubo Ma and Yue He Correction: Cancer Imaging (2023) 23:34 data XZ, JF, YP, and XG. Drafting of the manuscript: FX. https://doi.org/10.1186/s40644-023-00552-z Critical revision of the manuscript: YM, and YH. The original publication of this article contained an incorrect author contribution section. The incorrect and correct information is listed below. The original publica - tion [1] has been updated. Incorrect References NA designed the research, collected data, organized 1. Xu F, Peng L, Feng J, et al. A prediction model of nodal metastasis in cN0 oral the data on the computer, did the analysis, interpretation, squamous cell carcinoma using metabolic and pathological variables. Cancer Imaging. 2023;23:34. https://doi.org/10.1186/s40644-023-00552-z and identification, and wrote the draft manuscript. WT proposed the research concept, read the draft, reviewed, edited, supervised, and validated the final manuscript. Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in Correct published maps and institutional affiliations. Study concept and design: FX, YM and YH. Acquisition of data: FX, LP, and YH. Analysis and interpretation of Feng Xu and Liling Peng contributed equally to this work. The online version of the original article can be found at https://doi. org/10.1186/s40644-023-00552-z. *Correspondence: Yubo Ma mayb1566@126.com Yue He william5218@126.com Department of Nuclear Medicine, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China Shanghai Universal Medical Imaging Diagnostic Center, Shanghai, China Department of Oral Pathology, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China Department of Oral Maxillofacial & Head and Neck Oncology, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Cancer Imaging Springer Journals

Correction: A prediction model of nodal metastasis in cN0 oral squamous cell carcinoma using metabolic and pathological variables

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Springer Journals
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Copyright © The Author(s) 2023
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10.1186/s40644-023-00563-w
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Abstract

Xu et al. Cancer Imaging (2023) 23:47 Cancer Imaging https://doi.org/10.1186/s40644-023-00563-w Open Access C ORREC TION Correction: A prediction model of nodal metastasis in cN0 oral squamous cell carcinoma using metabolic and pathological variables 1† 2† 1 1 1 3 2 1* 4* Feng Xu , Liling Peng , Junyi Feng , Xiaochun Zhu , Yifan Pan , Yuhua Hu , Xin Gao , Yubo Ma and Yue He Correction: Cancer Imaging (2023) 23:34 data XZ, JF, YP, and XG. Drafting of the manuscript: FX. https://doi.org/10.1186/s40644-023-00552-z Critical revision of the manuscript: YM, and YH. The original publication of this article contained an incorrect author contribution section. The incorrect and correct information is listed below. The original publica - tion [1] has been updated. Incorrect References NA designed the research, collected data, organized 1. Xu F, Peng L, Feng J, et al. A prediction model of nodal metastasis in cN0 oral the data on the computer, did the analysis, interpretation, squamous cell carcinoma using metabolic and pathological variables. Cancer Imaging. 2023;23:34. https://doi.org/10.1186/s40644-023-00552-z and identification, and wrote the draft manuscript. WT proposed the research concept, read the draft, reviewed, edited, supervised, and validated the final manuscript. Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in Correct published maps and institutional affiliations. Study concept and design: FX, YM and YH. Acquisition of data: FX, LP, and YH. Analysis and interpretation of Feng Xu and Liling Peng contributed equally to this work. The online version of the original article can be found at https://doi. org/10.1186/s40644-023-00552-z. *Correspondence: Yubo Ma mayb1566@126.com Yue He william5218@126.com Department of Nuclear Medicine, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China Shanghai Universal Medical Imaging Diagnostic Center, Shanghai, China Department of Oral Pathology, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China Department of Oral Maxillofacial & Head and Neck Oncology, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Journal

Cancer Imaging – Springer Journals

Published: May 19, 2023

References