Regulation of artificial intelligence in healthcare: Clinical Laboratory Improvement Amendments (CLIA) as a model
A CLIA-like approach to regulating clinical AI would be complementary to the more centralized schemes currently under consideration, and it would ensure institutional and professional accountability for the longitudinal quality management of clinical AI.
Authors
- Anthony Solomonides (ORCID: https://orcid.org/0000-0003-2117-2461)
- Suresh Balu (ORCID: https://orcid.org/0000-0003-4929-9130)
- Dean F. Sittig (ORCID: https://orcid.org/0000-0001-5811-8915)
- Mark Sendak (ORCID: https://orcid.org/0000-0001-5828-4497)
- Brian R. Jackson (ORCID: https://orcid.org/0000-0001-7902-3990)
Institutions
- Duke University (US)
- University of Utah (US)
- Duke Institute for Health Innovation (US)
- The University of Texas Health Science Center at Houston (US)
Publication Details
- Journal
- Journal of the American Medical Informatics Association
- Published
- 2024-12-06
- DOI
- https://doi.org/10.1093/jamia/ocae296
- Citations
- 10
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 1.20