Patient and clinician perspectives in the use of machine learning and artificial intelligence in the context of acute neurology
Patients and clinicians expressed mixed views about ML/AI. Potential benefits related to improved decision-making and concerns focused on bias, liability, and the need for further education. Future work should address how best to incorporate ML/AI into education and obviate potential burdens as ML/AI is integrated into clinical care.
Authors
- Andrew M. Naidech (ORCID: https://orcid.org/0000-0003-1065-5417)
- Egide Abahuje (ORCID: https://orcid.org/0000-0001-5527-5405)
- William K. Thompson (ORCID: https://orcid.org/0000-0002-5603-423X)
- Kelly N. Michelson (ORCID: https://orcid.org/0000-0002-9714-9535)
- Ethan J. Houskamp (ORCID: https://orcid.org/0000-0002-2090-562X)
- Juliana Silva Pinheiro do Nascimento
- Elaf Agha
Institutions
- Northwestern University (US)
- University of Michigan (US)
- Kellogg's (Canada) (CA)
- Michigan Medicine (US)
- Lurie Children's Hospital (US)
Publication Details
- Journal
- JAMIA Open
- Published
- 2025-11-03
- DOI
- https://doi.org/10.1093/jamiaopen/ooaf143
- Citations
- 1
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.65