Authors’ Reply: Critical Limitations in Comparing ChatGPT and DeepSeek for Orthopedic Assessment
We respond to comments on our study comparing ChatGPT and DeepSeek for answering orthopedic multiple-choice questions. We clarify that the reported Cohen κ values reflect inter-rater reliability within each model rather than agreement between the two models. All questions were administered in English, and the findings therefore reflect performance in an English-language context. We acknowledge limitations related to reproducibility due to the use of web-based interfaces and address concerns about data contamination. We also correct a typographical error in the reported accuracy for the pelvic and spine injury category.
Authors
- Chirathit Anusitviwat (ORCID: https://orcid.org/0000-0001-6730-7486)
- Boonsin Tangtrakulwanich (ORCID: https://orcid.org/0000-0003-0933-1669)
- Jongdee Bvonpanttarananon (ORCID: https://orcid.org/0000-0001-6692-8627)
- Sitthiphong Suwannaphisit (ORCID: https://orcid.org/0000-0002-4895-5987)
Institutions
- Prince of Songkla University (TH)
- Navamindradhiraj University (TH)
Publication Details
- Journal
- JMIR Formative Research
- Published
- 2026-03-17
- DOI
- https://doi.org/10.2196/91470
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00