Ingman Wendy V, Britt Kara L, Stone Jennifer, Nguyen Tuong L, Hopper John L, Thompson Erik W
Discipline of Surgical Specialities, Adelaide Medical School, University of Adelaide, The Queen Elizabeth Hospital, Adelaide 5011, Australia; Robinson Research Institute, University of Adelaide, Adelaide 5005, Australia.
Breast Cancer Risk and Prevention Laboratory, Peter MacCallum Cancer Centre, Melbourne 3000, Australia; Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville 3000, Australia; Department of Anatomy and Developmental Biology, Monash University Clayton, Clayton 3800, Australia.
Trends Cancer. 2025 Mar;11(3):188-191. doi: 10.1016/j.trecan.2024.10.007. Epub 2024 Dec 12.
Artificial intelligence (AI) is enabling us to delve deeply into the information inherent in a mammogram and identify novel features associated with high risk of a future breast cancer diagnosis. Here, we discuss how AI is improving mammographic density-associated risk prediction and shaping the future of screening and risk-reducing strategies.
人工智能（AI）使我们能够深入探究乳房X光检查中固有的信息，并识别与未来乳腺癌诊断高风险相关的新特征。在此，我们讨论人工智能如何改善与乳房X光密度相关的风险预测，以及如何塑造筛查和降低风险策略的未来。
