Performance of generative artificial intelligence in oral and maxillofacial radiology based on the board-certification examination of Japan
OBJECTIVE: To evaluate the performance and potential utility of generative artificial intelligence (AI) in oral and maxillofacial radiology using the board-certification examination administered by the Japanese Society for Oral and Maxillofacial Radiology (JSOMR). METHODS: The responses generated by ChatGPT for multiple-choice questions from the board-certification examination of the JSOMR over the three-year period from 2020 to 2022 were assessed. The questions were manually entered individually as prompts for GPT-3.5, GPT-4, and GPT-5, which are the models available from ChatGPT. The accuracy was calculated according to examination year, question format, and level of taxonomy. RESULTS: GPT-3.5 achieved an accuracy of 40.3% for the three years (42.9%, 42.0%, and 36.0% for 2020, 2021, and 2022, respectively), that of GPT-4 was 67.8% (67.3%, 74.0%, and 62.0%, respectively), and that of GPT-5 was 76.5% (79.6%, 78.0%, and 72.0%, respectively). GPT-5's results exceeded the passing score for each year with the accuracy significantly outperformed that of GPT-3.5 and GPT-4. Regarding performance according to the question format, GPT-5 performed significantly superior to the earlier models, especially on two-answer questions. CONCLUSIONS: On the board-certification examination of the JSOMR, the performance of GPT-5 was significantly superior to that of GPT-3.5 and GPT-4. This suggests that, given the rapid development of generative AI, GPT-5 has reached a level of text-based knowledge equivalent to that assessed in the board-certification examination of the JSOMR.
Authors
- Yohei Takeshita (ORCID: https://orcid.org/0000-0002-9345-5797)
- Yuri Namba
- Akira Shibanuma (ORCID: https://orcid.org/0000-0003-2058-1722)
- Yoshinobu Yanagi (ORCID: https://orcid.org/0000-0001-7129-5115)
- Toshiyuki Kawazu (ORCID: https://orcid.org/0000-0002-2749-2805)
- Yoshihide Nakamura (ORCID: https://orcid.org/0009-0007-4180-5509)
- Mamiko Fujikura
- Shunsuke Okada (ORCID: https://orcid.org/0000-0001-8056-4305)
- Miki Hisatomi (ORCID: https://orcid.org/0000-0002-9112-5145)
- Saori Yoshida (ORCID: https://orcid.org/0000-0002-4504-6243)
- Suzuka Yoshida
Institutions
- Okayama University (JP)
- Okayama University Hospital (JP)
- The University of Tokyo (JP)
Publication Details
- Journal
- Oral Radiology
- Published
- 2026-08-20
- DOI
- https://doi.org/10.1007/s11282-026-00965-z
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Okayama University