Assessment of ChatGPT-4 in Family Medicine Board Examinations Using Advanced AI Learning and Analytical Methods: Observational Study
The study demonstrates that ChatGPT-4, particularly when equipped with specialized preparation and when operating in a tailored subenvironment, shows promising potential in handling the intricacies of medical board examinations. While its performance is comparable with the expected standards for passing the ABFM Certification Examination, further enhancements in AI technology and tailored training methods could push these capabilities to new heights. This exploration opens avenues for integrating AI tools such as ChatGPT-4 in medical education and assessment, emphasizing the importance of continuous advancement and specialized training in medical applications of AI.
Authors
- Sten Kajitani (ORCID: https://orcid.org/0009-0007-5752-6432)
- Anthony James Goodings (ORCID: https://orcid.org/0009-0005-9702-0968)
- Allison Dana Chhor
- Mila Pastrak (ORCID: https://orcid.org/0009-0005-4423-8197)
- Megha Kodancha (ORCID: https://orcid.org/0009-0002-4639-7499)
- Rowan Ives (ORCID: https://orcid.org/0009-0008-6353-3935)
- Yoo Bin Lee (ORCID: https://orcid.org/0000-0002-4789-1715)
- Ahmad Albakri
- Kari Kajitani
Institutions
- University of Ottawa (CA)
- University College Cork (IE)
- University of California San Diego (US)
- St. John's College (US)
Publication Details
- Journal
- JMIR Medical Education
- Published
- 2024-08-15
- DOI
- https://doi.org/10.2196/56128
- Citations
- 8
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.96