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Artificial intelligence improves mammography-based breast cancer risk prediction.

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Title: Artificial intelligence improves mammography-based breast cancer risk prediction.
Authors: Ingman WV; 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., Britt KL; 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., Stone J; Genetic Epidemiology Group, School of Population and Global Health, University of Western Australia, Perth 6009, Australia., Nguyen TL; Melbourne School of Population and Global Health, University of Melbourne, Melbourne 3010, Australia., Hopper JL; Melbourne School of Population and Global Health, University of Melbourne, Melbourne 3010, Australia., Thompson EW; School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane 4059, Australia; Translational Research Institute, Woolloongabba 4102, Australia. Electronic address: e2.thompson@qut.edu.au.
Source: Trends in cancer [Trends Cancer] 2025 Mar; Vol. 11 (3), pp. 188-191. Date of Electronic Publication: 2024 Dec 12.
Publication Type: Journal Article; Review
Journal Info: Publisher: Cell Press Country of Publication: United States NLM ID: 101665956 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2405-8025 (Electronic) Linking ISSN: 24058025 NLM ISO Abbreviation: Trends Cancer Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Artificial intelligence improves mammography-based breast cancer risk prediction.
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  Data: <searchLink fieldCode="AU" term="%22Ingman+WV%22">Ingman WV</searchLink>; 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.<br /><searchLink fieldCode="AU" term="%22Britt+KL%22">Britt KL</searchLink>; 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.<br /><searchLink fieldCode="AU" term="%22Stone+J%22">Stone J</searchLink>; Genetic Epidemiology Group, School of Population and Global Health, University of Western Australia, Perth 6009, Australia.<br /><searchLink fieldCode="AU" term="%22Nguyen+TL%22">Nguyen TL</searchLink>; Melbourne School of Population and Global Health, University of Melbourne, Melbourne 3010, Australia.<br /><searchLink fieldCode="AU" term="%22Hopper+JL%22">Hopper JL</searchLink>; Melbourne School of Population and Global Health, University of Melbourne, Melbourne 3010, Australia.<br /><searchLink fieldCode="AU" term="%22Thompson+EW%22">Thompson EW</searchLink>; School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane 4059, Australia; Translational Research Institute, Woolloongabba 4102, Australia. Electronic address: e2.thompson@qut.edu.au.
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  Data: <searchLink fieldCode="JN" term="%22101665956%22">Trends in cancer</searchLink> [Trends Cancer] 2025 Mar; Vol. 11 (3), pp. 188-191. <i>Date of Electronic Publication: </i>2024 Dec 12.
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        Value: 10.1016/j.trecan.2024.10.007
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              Text: 2025 Mar
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