ArticleFrontiers in oral health2025
Brush, byte, and bot: quality comparison of artificial intelligence-generated pediatric dental advice across ChatGPT, Gemini, and Copilot.
Article in Frontiers in oral health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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Who cites it
6 citing papers in PubMed.
- The Role of Large Language Models in Identifying and Correcting Paediatric Health Misinformation for Parents: A Paediatric Nursing Perspective.Journal of paediatrics and child health · 2026Article
- Performance of three large language models in answering parent-focused questions on rickets: a dual pediatric-orthopedic specialist evaluation.BMC pediatrics · 2026Article
- Comparative diagnostic accuracy of multiple large language models in oral and maxillofacial radiology specialty examinations: a 13-year analysis of performance and topic trends.BMC oral health · 2026Article
- Comparative performance of large language models for patient-oriented support in dental trauma emergencies.BMC oral health · 2026Article
- Artificial Intelligence-Aided Tooth Detection and Segmentation on Pediatric Panoramic Radiographs in Mixed Dentition Using a Transfer Learning Approach.Diagnostics (Basel, Switzerland) · 2025Article
- Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Artificial intelligence (AI) tools such as ChatGPT, Google Gemini, and Microsoft Copilot are increasingly relied upon by parents for immediate guidance on pediatric dental concerns. This study evaluated and compared the response quality of these AI platforms in addressing real-world parental queries related to pediatric dentistry, including early tooth extraction, space maintenance, and the decision to consult a pediatric or a general dentist. Methods: A structured 30-question survey was developed and submitted to each AI model, and their responses were anonymized and assessed by pediatric dental experts using a standardized rubric across five key domains: clinical accuracy, clarity, completeness, relevance, and absence of misleading information. Results: Statistically significant differences were found across all five domains ( Discussion: While AI technologies show potential as clinical decision support systems, their variable performance reinforces the need for expert oversight. Future AI development should focus on optimizing response quality and safety to ensure effective and trustworthy digital health communication for pediatric dental care.
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What Socratic 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 Socratic graph.