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Authors
Wang, Lijun
Chang, Lufan
Luo, Ran
Cui, Xuee
Liu, Huanhuan
Wu, Haoting
Chen, Yanhong
Zhang, Yuzhen
Wu, Chenqing
Li, Fangzhen
Liu, Hao
Guan, Wenbin
Wang, Dengbin https://orcid.org/0000-0002-0790-9554
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Funding
Funding for this research was provided by:
shanghai municipal commission of heath and family planning on medical intelligence (2018ZHYL0108)
doctoral innovation fund of shanghai jiao tong university school of medicine (CBXJ201807)
Program of Shanghai Science and Technology Committee (No. 21S31905000)
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Article History
Received: 22 July 2021
Revised: 20 December 2021
Accepted: 21 December 2021
First Online: 8 March 2022
Declarations
: This retrospective study was approved by the institutional review board of our hospital, and the need to obtain informed consent was waived (approval #, XHEC-D-2020-104). This study was in accordance with the Declaration of Helsinki.
: The scientific guarantor of this publication is Dengbin Wang, MD, PhD, the chief of the Department of Radiology, Xinhua Hospital affiliated to Shanghai Jiao Tong University School of Medicine.
: All the authors in this research declare no potential conflicts of interest on the work. Two authors of this research, Lufan Chang and Hao Liu, work for a medical company (Yizhun Medical AI Co. Ltd., Beijing, China). No disclosures of potential conflicts of Yizhun Medical AI Co. Ltd., Beijing, China, and no other potential conflict of interest relevant to this article are reported.
: No complex statistical methods were necessary for this paper.
: Written informed consent was waived by the institutional review board.
: Institutional Review Board approval was obtained.
: Eleven patients included in this study overlap with a prior study. The prior study focused on describing the MRI features of papillary breast lesions. This study focused on developing a deep learning model for the classification of NME lesions. We have uploaded the PDF of this study in the online submission system.
: • retrospective• diagnostic or prognostic study• performed at one institution
