Deep Learning Based on Automated Breast Volume Scanner Images for the Diagnosis of Breast Lesions: A Multicenter Diagnostic Study.

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Title: Deep Learning Based on Automated Breast Volume Scanner Images for the Diagnosis of Breast Lesions: A Multicenter Diagnostic Study.
Authors: Liu H; Department of Medical Ultrasound, Center of Minimally Invasive Treatment for Tumor, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200072, China.; Ultrasound Research and Education Institute, Clinical Research Center for Interventional Medicine, School of Medicine, Tongji University Shanghai 200072, China., Zhang Y; Department of Medical Ultrasound, Center of Minimally Invasive Treatment for Tumor, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200072, China.; Ultrasound Research and Education Institute, Clinical Research Center for Interventional Medicine, School of Medicine, Tongji University Shanghai 200072, China., Tan B; MedAI Technology (Wuxi) Co. Ltd, Wuxi, China., Yin YF; Department of Medical Ultrasound, Affiliated Hospital of Nantong University, Nantong, 226001, China., Yan LX; Department of Ultrasound, Institute of Ultrasound in Medicine and Engineering, Zhongshan Hospital, Fudan University, Shanghai 200032, China., Xiang LH; Department of Medical Ultrasound, Center of Minimally Invasive Treatment for Tumor, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200072, China.; Ultrasound Research and Education Institute, Clinical Research Center for Interventional Medicine, School of Medicine, Tongji University Shanghai 200072, China., Shan DD; Department of Medical Ultrasound, Center of Minimally Invasive Treatment for Tumor, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200072, China.; Ultrasound Research and Education Institute, Clinical Research Center for Interventional Medicine, School of Medicine, Tongji University Shanghai 200072, China., Zhang YY; Department of Medical Ultrasound, Center of Minimally Invasive Treatment for Tumor, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200072, China.; Ultrasound Research and Education Institute, Clinical Research Center for Interventional Medicine, School of Medicine, Tongji University Shanghai 200072, China., Ding SS; Department of Medical Ultrasound, Center of Minimally Invasive Treatment for Tumor, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200072, China.; Ultrasound Research and Education Institute, Clinical Research Center for Interventional Medicine, School of Medicine, Tongji University Shanghai 200072, China., Xu G; Department of Medical Ultrasound, Center of Minimally Invasive Treatment for Tumor, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200072, China.; Ultrasound Research and Education Institute, Clinical Research Center for Interventional Medicine, School of Medicine, Tongji University Shanghai 200072, China., Zhou BY; Department of Ultrasound, Institute of Ultrasound in Medicine and Engineering, Zhongshan Hospital, Fudan University, Shanghai 200032, China., Shi YL; MedAI Technology (Wuxi) Co. Ltd, Wuxi, China., Zhu XX; Chair of Data Science in Earth Observation, Technical University of Munich, Germany., Hu JL; MedAI Technology (Wuxi) Co. Ltd, Wuxi, China., Sun LP; Department of Medical Ultrasound, Center of Minimally Invasive Treatment for Tumor, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200072, China.; Ultrasound Research and Education Institute, Clinical Research Center for Interventional Medicine, School of Medicine, Tongji University Shanghai 200072, China., Xu HX; Department of Ultrasound, Institute of Ultrasound in Medicine and Engineering, Zhongshan Hospital, Fudan University, Shanghai 200032, China., Zhang YF; Department of Ultrasound, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China.
Source: International journal of medical sciences [Int J Med Sci] 2025 Aug 22; Vol. 22 (15), pp. 3924-3937. Date of Electronic Publication: 2025 Aug 22 (Print Publication: 2025).
Publication Type: Journal Article; Multicenter Study; Randomized Controlled Trial
Journal Info: Publisher: Ivyspring International Publisher Country of Publication: Australia NLM ID: 101213954 Publication Model: eCollection Cited Medium: Internet ISSN: 1449-1907 (Electronic) Linking ISSN: 14491907 NLM ISO Abbreviation: Int J Med Sci Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1449-1907
DOI:10.7150/ijms.118430