Authors' Reply to: Variability in Large Language Models' Responses to Medical Licensing and Certification Examinations

Aidan Gilson; Conrad W Safranek; Thomas Huang; Vimig Socrates; Ling Chi; Richard Andrew Taylor; David Chartash

doi:10.2196/50336

Authors' Reply to: Variability in Large Language Models' Responses to Medical Licensing and Certification Examinations

JMIR Med Educ. 2023 Jul 13:9:e50336. doi: 10.2196/50336.

Authors

Aidan Gilson^{1

2}, Conrad W Safranek¹, Thomas Huang², Vimig Socrates^{1

3}, Ling Chi¹, Richard Andrew Taylor^#^{1

2}, David Chartash^#^{1

4}

Affiliations

¹ Section for Biomedical Informatics and Data Science, Yale University School of Medicine, New Haven, CT, United States.
² Department of Emergency Medicine, Yale University School of Medicine, New Haven, CT, United States.
³ Program of Computational Biology and Bioinformatics, Yale University, New Haven, CT, United States.
⁴ School of Medicine, University College Dublin, National University of Ireland, Dublin, Dublin, Ireland.

^# Contributed equally.

PMID: 37440299
PMCID: PMC10375396
DOI: 10.2196/50336

No abstract available

Keywords: AI; ChatGPT; GPT; MedQA; NLP; artificial intelligence; chatbot; conversational agent; education technology; generative pre-trained transformer; knowledge assessment; large language models; machine learning; medical education; natural language processing.

Grants and funding

UL1 TR001863/TR/NCATS NIH HHS/United States