Skip to main content
Nature Communications logoLink to Nature Communications
. 2021 Jul 12;12:4370. doi: 10.1038/s41467-021-24605-8

Author Correction: Deep learning radiomics can predict axillary lymph node status in early-stage breast cancer

Xueyi Zheng 1,#, Zhao Yao 2,#, Yini Huang 1,#, Yanyan Yu 3,#, Yun Wang 1, Yubo Liu 1, Rushuang Mao 1, Fei Li 1, Yang Xiao 3, Yuanyuan Wang 2,4, Yixin Hu 1, Jinhua Yu 2,4,, Jianhua Zhou 1,
PMCID: PMC8275735  PMID: 34253726

Correction to: Nature Communications 10.1038/s41467-020-15027-z, Published online 06 March 2020.

This Article contained an error in the Supplementary Software. The deep learning radiomics software for predicting axillary lymph node status was damaged when the files were compressed during the submission process. The original code availability statement stated that the code was provided in two separate files, the code is now provided in one file. The software has now been corrected and the Code Availability statement has been corrected to read ‘The software and code of the proposed method are available as Supplementary Software’.

Supplementary information

Supplementary software (554.5MB, zip)

Footnotes

The original article can be found online at 10.1038/s41467-020-15027-z.

These authors contributed equally: Xueyi Zheng, Zhao Yao, Yini Huang, Yanyan Yu.

Contributor Information

Jinhua Yu, Email: jhyu@fudan.edu.cn.

Jianhua Zhou, Email: zhoujh@sysucc.org.cn.

Supplementary information

The online version contains supplementary material available at 10.1038/s41467-021-24605-8.

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary software (554.5MB, zip)

Articles from Nature Communications are provided here courtesy of Nature Publishing Group

RESOURCES