TY - JOUR AU - Niu, Sihua AU - Huang, Jianhua AU - Li, Jia AU - Liu, Xueling AU - Wang, Dan AU - Zhang, Ruifang AU - Wang, Yingyan AU - Shen, Huiming AU - Qi, Min AU - Xiao, Yi AU - Guan, Mengyao AU - Liu, Haiyan AU - Li, Diancheng AU - Liu, Feifei AU - Wang, Xiuming AU - Xiong, Yu AU - Gao, Siqi AU - Wang, Xue AU - Zhu, Jiaan PY - 2020 DA - 2020/10/02 TI - Application of ultrasound artificial intelligence in the differential diagnosis between benign and malignant breast lesions of BI-RADS 4A JO - BMC Cancer SP - 959 VL - 20 IS - 1 AB - The classification of Breast Imaging Reporting and Data System 4A (BI-RADS 4A) lesions is mostly based on the personal experience of doctors and lacks specific and clear classification standards. The development of artificial intelligence (AI) provides a new method for BI-RADS categorisation. We analysed the ultrasonic morphological and texture characteristics of BI-RADS 4A benign and malignant lesions using AI, and these ultrasonic characteristics of BI-RADS 4A benign and malignant lesions were compared to examine the value of AI in the differential diagnosis of BI-RADS 4A benign and malignant lesions. SN - 1471-2407 UR - https://doi.org/10.1186/s12885-020-07413-z DO - 10.1186/s12885-020-07413-z ID - Niu2020 ER -