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

Autor: Zheng X; Department of Ultrasound, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China., Yao Z; Department of Electronic Engineering, Fudan University, Shanghai, China., Huang Y; Department of Ultrasound, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China., Yu Y; Paul C. Lauterbur Research Center for Biomedical Imaging, Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China., Wang Y; Department of Ultrasound, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China., Liu Y; Department of Ultrasound, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China., Mao R; Department of Ultrasound, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China., Li F; Department of Ultrasound, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China., Xiao Y; Paul C. Lauterbur Research Center for Biomedical Imaging, Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China., Wang Y; Department of Electronic Engineering, Fudan University, Shanghai, China.; The key laboratory of medical imaging computing and computer assisted intervention of Shanghai, Shanghai, China., Hu Y; Department of Ultrasound, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China., Yu J; Department of Electronic Engineering, Fudan University, Shanghai, China. jhyu@fudan.edu.cn.; The key laboratory of medical imaging computing and computer assisted intervention of Shanghai, Shanghai, China. jhyu@fudan.edu.cn., Zhou J; Department of Ultrasound, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China. zhoujh@sysucc.org.cn.
Jazyk: angličtina
Zdroj: Nature communications [Nat Commun] 2021 Jul 12; Vol. 12 (1), pp. 4370. Date of Electronic Publication: 2021 Jul 12.
DOI: 10.1038/s41467-021-24605-8
Databáze: MEDLINE