Acceptability of artificial intelligence in breast screening: focus groups with the screening-eligible population in England
It will be essential that future decision-making and communication about AI implementation in breast screening (and, likely, in healthcare more widely) address concerns surrounding (1) the fallibility of AI, (2) lack of inclusion, control and transparency in relation to healthcare and technology decisions and (3) humans being left redundant and unneeded, while building on women's hopes for the technology.
Authors
- Lauren Gatting (ORCID: https://orcid.org/0000-0003-3693-2013)
- Angie A. Kehagia (ORCID: https://orcid.org/0000-0002-5142-7456)
- Syeda Ahmed
- Jo Waller (ORCID: https://orcid.org/0000-0003-4025-9132)
- Rumana Newlands (ORCID: https://orcid.org/0000-0003-4563-152X)
- Priscilla Meccheri
Institutions
- Queen Mary University of London (GB)
- King's College London (GB)
- University of Aberdeen (GB)
- London Cancer (GB)
- King's College School (GB)
Publication Details
- Journal
- BMJ Public Health
- Published
- 2024-12-01
- DOI
- https://doi.org/10.1136/bmjph-2024-000892
- Citations
- 9
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 3.13
Funders
- Department of Health and Social Care