Implementing artificial intelligence in breast cancer screening: Women’s preferences
The 802 participants preferred screening where AI was more accurate, Australian owned, more representative and had shorter waiting time for results (all p < .001). There were strong preferences (p < .001) against AI alone or as triage. Three patterns of preferences emerged: positive about AI if accuracy improves (40% of sample), strongly against AI (42%), and concerned about AI (18%). Participants were willing to accept AI replacing one human reader if their results were available 10 days faster than current practice but would need results 21 days faster for AI as triage. Implementing AI inconsistent with community preferences could reduce participation by up to 22%.
Authors
- Stacy M. Carter (ORCID: https://orcid.org/0000-0003-2617-8694)
- Nehmat Houssami (ORCID: https://orcid.org/0000-0002-3641-952X)
- M. Luke Marinovich (ORCID: https://orcid.org/0000-0002-3801-8180)
- Mary Macheras‐Magias
- Alison Pearce (ORCID: https://orcid.org/0000-0002-5690-9542)
- Helen Frazer (ORCID: https://orcid.org/0000-0001-9399-8102)
- Gary D. Webb
Institutions
- The University of Sydney (AU)
- New South Wales Department of Health (AU)
- University of Wollongong (AU)
- Breast Cancer Network Australia (AU)
- St Vincent's Hospital Melbourne (AU)
- Breastscreen Victoria (AU)
- Cancer Council NSW (AU)
Publication Details
- Journal
- Cancer
- Published
- 2025-04-22
- DOI
- https://doi.org/10.1002/cncr.35859
- Citations
- 6
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 3.93
Funders
- National Breast Cancer Foundation
- University of Sydney
- Medical Research Council
- National Health and Medical Research Council