ArticleBMC oral health2026
Artificial intelligence chatbots versus dentists: a comparative knowledge assessment on traumatic dental injury management.
Article in BMC oral health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Impact of guideline-based prompting on the large language model performance in dental trauma management clinical decision-making.Odontology · 2026Article
- Large language models and generative artificial intelligence in endodontics: a scoping review.Odontology · 2026Review
- ChatGPT in Pediatric Dental Trauma: A Cross-Sectional Assessment of Response Reliability to Parental Queries.Cureus · 2026Article
- Evaluation of the approaches of different specialties and artificial intelligence systems on traumatic dental injuries.BMC oral health · 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
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe aim of this study is to conduct a comparative analysis of the guideline-based knowledge levels of dentists and artificial intelligence(AI)-powered chatbots (ChatGPT-4o and Gemini) regarding the emergency management of traumatic dental injuries (TDIs).
methodsA 20-item multiple-choice questionnaire, developed based on the trauma guidelines recommended by the American Association of Endodontists (AAE), was administered to both AI-powered chatbots (ChatGPT-4o and Gemini) and practicing dentists. The guideline-based knowledge level and consistency of the AI responses were evaluated based on the collected data. Furthermore, the knowledge levels of the AI systems were statistically compared to those of the dentists, using a significance level of p < 0.05 and a 95% confidence interval.
resultsUpon analysis of the questionnaire responses, ChatGPT-4o provided significantly more correct answers than both dentists and Gemini in 17 out of the 20 questions (p < 0.05). There was a statistically significant difference in guideline-based knowledge levels among the groups (p = 0.001; p < 0.05). The rate of high-level knowledge demonstrated by ChatGPT-4o (100%) was statistically significantly greater than that of both dentists (12.6%) and Gemini (3.4%) (p < 0.05). ChatGPT-4o exhibited similar internal consistency score to Gemini in terms of reliability.
conclusionsChatGPT-4o and Gemini may be considered potential sources of information in the context of TDIs. Although ChatGPT-4o provided significantly more accurate and consistent responses compared to Gemini, it is not entirely sufficient. Further research involving AI models specifically developed for the field of endodontics is necessary to address current limitations.
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.