ArticleJournal of evaluation in clinical practice2025
Evaluation of Artificial Intelligence Conversational Models in Providing Information on Dental Implants: A Comparative Analysis of ChatGPT, Gemini and MedGebra.
Article in Journal of evaluation in clinical practice, 2025. 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.
- Accuracy and Short-Term Consistency of Generative AI Chatbots in Guideline-Based Endodontic Decision Support: A Multi-Model Benchmarking Study.Dentistry journal · 2026Article
- Large language models in implant dentistry: a scoping review of applications, performance, and limitations.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
5 authors.
Funding
Abstract
AIMS AND
objectivesThis cross-sectional study aims to compare the accuracy, precision and clarity of responses to dental implant questions from three artificial intelligence (AI) models: ChatGPT (OpenAI, GPT-4), Gemini (Google) and MedGebra. MATERIALS AND
methods56 questions from an EAO patient guide were used and responses from each AI system were evaluated independently by two oral surgery specialists using a four-point Likert scale for correctness, precision and clarity.
resultsChatGPT consistently scored highest especially in clarity with perfect marks from both evaluators. Gemini ranked lower in accuracy and precision but exhibited similar clarity. MedGebra received the lowest ratings on all criteria. Though consistency generally remained excellent, the inter-rater reliability study revealed some variance in agreement levels between two examiners.
conclusionChatGPT and Gemini provided more accurate and informative responses on dental implants questions compared to MedGebra. According to the findings of the present study AI chatbots have potential for enhancing patient education on dental implants but professional oversight is crucial for ensuring accuracy and reliability. The study highlights the promising and potential benefits of large language models (LLMs) in dental patient education.
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.