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Radiologist and AI Concordance in Screening Mammography and Association with Future Breast Cancer Risk.

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Title: Radiologist and AI Concordance in Screening Mammography and Association with Future Breast Cancer Risk.
Authors: Kim EY; Department of Surgery, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea., Park EK; Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea.; Healthcare AI Research Institute, Seoul National University Hospital, Seoul, Republic of Korea., Kwon MR; Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea., Kim M; Lunit, Seoul, Republic of Korea.; Department of Statistics, Ewha Womans University, Seoul, Republic of Korea., Park J; Center for Cohort Studies, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea., Kang J; Center for Cohort Studies, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea., Cho Y; Center for Cohort Studies, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.; Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea., Lee S; Lunit, Seoul, Republic of Korea., Song M; Lunit, Seoul, Republic of Korea., Kim KH; Lunit, Seoul, Republic of Korea., Kim TS; Lunit, Seoul, Republic of Korea., Lee H; Lunit, Seoul, Republic of Korea., Kwon R; Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea.; Institute of Medical Research, Sungkyunkwan University School of Medicine, Suwon, Republic of Korea., Lim GY; Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea.; Institute of Medical Research, Sungkyunkwan University School of Medicine, Suwon, Republic of Korea., Choi J; School of Mechanical Engineering, Sunkyungkwan University, Republic of Korea., Ham SY; Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea., Kook SH; Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea., Chang Y; Center for Cohort Studies, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.; Department of Occupational and Environmental Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Samsung Main Building B2, 250, Taepyung-ro 2ga, Jung-gu, Seoul 04514, Republic of Korea.; Department of Clinical Research Design & Evaluation, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Seoul, Republic of Korea., Ryu S; Center for Cohort Studies, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.; Department of Occupational and Environmental Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Samsung Main Building B2, 250, Taepyung-ro 2ga, Jung-gu, Seoul 04514, Republic of Korea.; Department of Clinical Research Design & Evaluation, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Seoul, Republic of Korea.
Source: Radiology. Artificial intelligence [Radiol Artif Intell] 2025 Nov; Vol. 7 (6), pp. e240804.
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
Journal Info: Publisher: Radiological Society of North America, Inc Country of Publication: United States NLM ID: 101746556 Publication Model: Print Cited Medium: Internet ISSN: 2638-6100 (Electronic) Linking ISSN: 26386100 NLM ISO Abbreviation: Radiol Artif Intell Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2638-6100
DOI:10.1148/ryai.240804