Opinions of the UK general public and stroke survivors in using artificial intelligence and ‘opt-out’ models of consent in medical research: a qualitative study
The public and those with lived stroke/TIA experience appeared to support using deidentified medical datasets for AI-driven stroke risk prediction under an opt-out consent model. However, this is provided that the research conducted is transparent, for a clear medical purpose and adheres to strict data security measures.
Authors
- Megan Courtman (ORCID: https://orcid.org/0000-0002-8984-7798)
- Daniel Browning (ORCID: https://orcid.org/0009-0009-9261-773X)
- Emmanuel Ifeachor (ORCID: https://orcid.org/0000-0001-8362-6292)
- Michael Allen (ORCID: https://orcid.org/0000-0002-8746-9957)
- Stephen Mullin (ORCID: https://orcid.org/0000-0002-1936-394X)
- William Heseltine-Carp (ORCID: https://orcid.org/0000-0003-3119-9983)
- Aishwarya Kasabe (ORCID: https://orcid.org/0000-0003-1934-9723)
- Mark Thurtson
Institutions
- University of Exeter (GB)
- University of Plymouth (GB)
Publication Details
- Journal
- BMJ Open
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1136/bmjopen-2025-108671
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00