Generative AI in Medicine: Pioneering Progress or Perpetuating Historical Inaccuracies? Cross-Sectional Study Evaluating Implicit Bias
gAI created a sample population of physicians that underrepresented women when compared to both the resident and active physician workforce. Steps must be taken to train datasets in order to represent the diversity of the incoming physician workforce.
Authors
- Philip Anthony Sutera (ORCID: https://orcid.org/0000-0002-4021-5909)
- Timothy A. Lin (ORCID: https://orcid.org/0000-0003-4183-9120)
- Rohini Bhatia (ORCID: https://orcid.org/0000-0002-1444-7378)
- Reshma Jagsi (ORCID: https://orcid.org/0000-0001-6562-1228)
- Leslie Chang (ORCID: https://orcid.org/0000-0001-5963-054X)
- Andrea Brown
Institutions
- University of Minnesota (US)
- Emory Healthcare (US)
- The University of Texas MD Anderson Cancer Center (US)
- Johns Hopkins University (US)
- Emory University (US)
- Johns Hopkins Medicine (US)
- University of Rochester Medical Center (US)
Publication Details
- Journal
- JMIR AI
- Published
- 2025-05-17
- DOI
- https://doi.org/10.2196/56891
- Citations
- 1
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.65