Artificial Intelligence Algorithm for Subclinical Breast Cancer Detection
In this retrospective cohort study of women undergoing screening mammography, mean absolute AI scores were higher for breasts developing vs not developing cancer 4 to 6 years before their eventual detection. These findings suggest that commercial AI algorithms developed for breast cancer detection may identify women at high risk of a future breast cancer, offering a pathway for personalized screening approaches that can lead to earlier cancer diagnosis.
Authors
- Christoph I. Lee (ORCID: https://orcid.org/0000-0002-8185-7721)
- Solveig Hofvind (ORCID: https://orcid.org/0000-0003-0178-8939)
- Nataliia Moshina (ORCID: https://orcid.org/0000-0003-1477-1968)
- Diana L. Miglioretti (ORCID: https://orcid.org/0000-0002-5547-1833)
- Jonas Gjesvik (ORCID: https://orcid.org/0009-0005-6756-3566)
Institutions
- Norwegian Institute of Public Health (NO)
- Kaiser Permanente Washington Health Research Institute (US)
- University of Washington (US)
- Fred Hutch Cancer Center (US)
- Cancer Registry of Norway (NO)
- UiT The Arctic University of Norway (NO)
- University of California, Davis (US)
Publication Details
- Journal
- JAMA Network Open
- Published
- 2024-10-03
- DOI
- https://doi.org/10.1001/jamanetworkopen.2024.37402
- Citations
- 23
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 7.99