ArticleJournal of dental sciences2026
Comparison of the performances of different updated generative artificial intelligence models on the Japanese National Dental Examination.
Article in Journal of dental sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Generative Artificial Intelligence and Large Language Models in Paediatric Dentistry: A Scoping Review.International dental journal · 2026Article
- Diagnostic Capabilities of Large Language Models in Paediatric Dentistry.International dental journal · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background/purpose: Artificial intelligence (AI) has become widely used and applied in various fields. Although several studies have been conducted using generative AI for various qualification exams, to the best of our knowledge, none has focused on performance changes over time. Materials and methods: In August 2025, ChatGPT 5, Gemini 2.5, Microsoft Copilot, and Medi-Search were asked to answer compulsory questions from five years of the Japanese National Dental Examination. In 2024, we also conducted similar tests on other ChatGPT series and Gemini, and the scores were compared. Results: In 2025, Copilot, Gemini, and MediSearch scored 80 % or higher, which was the passing standard, for all five years. Although ChatGPT 3.5 did not meet the passing standard for any of the five years, ChatGPT 4o mini and ChatGPT 5 exceeded it for two and three years, respectively. In addition, both Chat GPT's and Gemini's scores substantially improved over time and with each update. Conclusion: This report suggests that generative AI is improving annually and adapting to the National Dental Examination. Although each AI model is suited to different fields, the trends may change over time. It is necessary to continue comparing and analyzing AI models and provide users with the latest information.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.