• Qiyu Liu, Meijing Qu, Lipeng Sun, and Hui Wang.
• Ultrasound Department of the First Affiliated Hospital of Dalian Medical University, Dalian City, Liaoning Province, China.
• Medicine (Baltimore). 2021 Dec 17; 100 (50): e28289e28289.

BackgroundArtificial intelligence system is a deep learning system based on computer-assisted ultrasonic image diagnosis, which can extract morphological features of breast mass and conduct objective and efficient image analysis, thus automatically intelligent classification of breast mass, avoiding subjective error and improving the accuracy of diagnosis.[1-2] A large number of studies have confirmed that artificial intelligence (AI) has high effectiveness and reliability in the differential diagnosis of benign and malignant breast diseases.[3-4] However, the results of these studies have been contradictory. Therefore, this meta-analysis tested the hypothesis that artificial intelligence system is accurate in distinguishing benign and malignant breast diseases.MethodsWe will search PubMed, Web of Science, Cochrane Library, and Chinese biomedical databases from their inceptions to the November 20, 2021, without language restrictions. Two authors will independently carry out searching literature records, scanning titles and abstracts, full texts, collecting data, and assessing risk of bias. Review Manager 5.2 and Stata14.0 software will be used for data analysis.ResultsThis systematic review will determine the accuracy of AI in the differential diagnosis of benign and malignant breast diseases.ConclusionIts findings will provide helpful evidence for the accuracy of AI in the differential diagnosis of benign and malignant breast diseases.Systematic Review RegistrationINPLASY2021110087.Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc.

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