Retrospective Study
Copyright ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Cases. Jan 14, 2022; 10(2): 518-527
Published online Jan 14, 2022. doi: 10.12998/wjcc.v10.i2.518
Diagnostic value of artificial intelligence automatic detection systems for breast BI-RADS 4 nodules
Shu-Yi Lyu, Yan Zhang, Mei-Wu Zhang, Bai-Song Zhang, Li-Bo Gao, Lang-Tao Bai, Jue Wang
Shu-Yi Lyu, Yan Zhang, Mei-Wu Zhang, Bai-Song Zhang, Li-Bo Gao, Lang-Tao Bai, Interventional Therapy Department, Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo 315010, Zhejiang Province, China
Shu-Yi Lyu, Yan Zhang, Mei-Wu Zhang, Bai-Song Zhang, Li-Bo Gao, Lang-Tao Bai, Interventional Therapy Department, Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo 315010, Zhejiang Province, China
Jue Wang, Ultrasonography Department, Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo 315010, Zhejiang Province, China
Jue Wang, Ultrasonography Department, Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo 315010, Zhejiang Province, China
Author contributions: Lyu SY designed and performed the research and wrote the paper; Zhang Y designed the research and supervised the report; Zhang MW and Zhang BS designed the research and contributed to the analysis; Gao LB and Bai LT collected data and contributed to the analysis; Wang J supervised the report.
Supported by Zhejiang Medical and Health Science and Technology Plan Project, No. 2020KY837 and No. 2020KY852.
Institutional review board statement: The study was approved by the ethics committee of Hwa Mei Hospital, University of Chinese Academy of Sciences (Approval No. pj-nbey-ky-2019-060-01).
Informed consent statement: All the subjects signed informed consent before the examination.
Conflict-of-interest statement: The authors declare that they have no conflict of interest to disclose.
Data sharing statement: Except the data in the text, no other data can be provided.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Yan Zhang, MD, Chief Doctor, Interventional Therapy Department, Hwa Mei Hospital, University of Chinese Academy of Sciences, No. 41 Northwest Street, Ningbo 315010, Zhejiang Province, China. wjcclsy@163.com
Received: September 14, 2021
Peer-review started: September 14, 2021
First decision: October 18, 2021
Revised: October 22, 2021
Accepted: November 29, 2021
Article in press: November 29, 2021
Published online: January 14, 2022
Processing time: 119 Days and 19.4 Hours
Core Tip

Core Tip: The accuracy of the AI-SONIC breast system in diagnosing BI-RADS 4 nodules is very high, which can improve the diagnostic accuracy of young doctors. It can also be used to upgrade and downgrade BI-RADS 4 nodules, guide clinical decision-making, reduce the biopsy rate for BI-RADS 4 nodules and prevent the waste of medical resources.