The PERFORM Study: Artificial Intelligence Versus Human Residents in Cross-Sectional Obstetrics-Gynecology Scenarios Across Languages and Time Constraints
High-performing AI LLMs reported strong diagnostic accuracy and resilience under linguistic and temporal pressures. These findings suggest that AI-enhanced decision-making may offer particular benefits in obstetrics and gynecology training programs, especially for junior residents, by improving diagnostic consistency and potentially reducing cognitive load in time-sensitive clinical settings.
Authors
- Sharon Raffaella Burk (ORCID: https://orcid.org/0000-0003-2242-8705)
- Giuseppe Vizzielli (ORCID: https://orcid.org/0000-0002-2424-2691)
- Antonio Giordano (ORCID: https://orcid.org/0000-0001-7143-6758)
- Vincenzo Carnevale (ORCID: https://orcid.org/0000-0002-0447-1278)
- Canio Martinelli (ORCID: https://orcid.org/0000-0002-0587-8467)
- Alfredo Ercoli (ORCID: https://orcid.org/0000-0002-5019-5526)
- L. Hermida Porto (ORCID: https://orcid.org/0009-0003-5002-9688)
Institutions
- University of Siena (IT)
- University of Messina (IT)
- University of Udine (IT)
- Temple University (US)
Publication Details
- Journal
- Mayo Clinic Proceedings Digital Health
- Published
- 2025-03-08
- DOI
- https://doi.org/10.1016/j.mcpdig.2025.100206
- Citations
- 3
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 1.96