Aug 2026· HRU International Journal of Dentistry and Oral Research· Vol 6, pp. 156-173· 0 citations· 34 references
TL;DR
AI-based chatbots may serve as supplementary tools for patient education on pediatric dental procedures such as pulpotomy and pulpectomy, and current models still have limitations concerning readability and reliability.
Abstract
Background: Parents increasingly consult publicly accessible artificial intelligence (AI) chatbots for information about their children’s dental treatment, and endodontic procedures in primary teeth are among the interventions that generate the greatest parental concern, so the quality of the information these tools deliver has direct consequences for informed decision-making. This study aimed to evaluate and compare the performance of four publicly accessible artificial intelligence (AI)-based chatbot platforms - Grok 3, Microsoft Copilot, ChatGPT (GPT-5) and Perplexity - in responding to frequently asked questions (FAQs) posed by parents regarding primary tooth endodontic treatments in pediatric dentistry.Materials and Methods: Inter-rater reliability was assessed using the intraclass correlation coefficient (ICC). Responses generated by the chatbots were evaluated using a standardized protocol. Accuracy was assessed using a 5-point Likert scale, quality using the Global Quality Scale (GQS), readability using the Flesch Reading Ease Score (FRES), and reliability using the modified DISCERN (mDISCERN) scale. A total of 20 categorized questions were individually submitted to each chatbot. All responses were independently evaluated by a specialist pediatric dentist and a pediatric dentistry research assistant. Because every question was submitted to all four platforms, related-samples methods were used: the Friedman test for accuracy, quality and reliability, and a one-way repeated-measures ANOVA with Greenhouse-Geisser correction for readability.Results: Inter-rater reliability between evaluators was excellent (ICC range across scales: 0.947-0.956; the 95% CI for each scale is given in Table 2). No statistically significant differences were observed among the chatbots regarding accuracy and quality (p>0.05). Readability differed significantly among the platforms in both question groups (overall p<0.05); in the pulpectomy group Microsoft Copilot was significantly more readable than Perplexity and Grok 3, whereas in the pulpotomy group no pairwise comparison remained significant after Bonferroni correction. Additionally, Perplexity showed superior reliability scores (p<0.001).Conclusions: AI-based chatbots may serve as supplementary tools for patient education on pediatric dental procedures such as pulpotomy and pulpectomy. Nevertheless, current models still have limitations concerning readability and reliability. Therefore, chatbot responses should be not only accurate but also clear and supported by credible sources, which is particularly important in health-related communication.
AI chatbots can generate information with potential clinical relevance in anterior implant dentistry; however, variability in informational reliability persists and expert supervision remains essential before integrating such tools into clinical education.
Dalndushe Abdulai, Raghıb Suradı, Mehran Moghbel· Journal of Health Sciences a...· 0 citations
AI-generated treatment plans should be regarded as adjunctive decision-support tools requiring specialist oversight before clinical implementation, and OpenEvidence and ChatGPT-5 demonstrated greater agreement with the expert reference standard, although clinically significant diagnostic errors were observed across all...
Sohil A. Kazim, Bashaer A Alnoman, Razan M Hashim et al.· Journal of Prosthodontics· 0 citations
BackgroundPectus excavatum and carinatum are the most common anterior chest wall deformities in children and adolescents. With growing awareness and easy access to online resources, patients increasingly seek information about these conditions from artificial intelligence platforms.ObjectiveThe aim of this study is to...
O. G. Illeez, E. Giray, U. Ateş et al.· Work· 0 citations
Objective: Although the integration of large language models (LLMs) into dental education is rapidly increasing, their actual performance in domain-specific assessments remains unclear. This study aimed to evaluate and compare the accuracy of four LLMs (ChatGPT-4.0, Gemini Advanced 1.5 Pro, DeepSeek-V3, and Perplexity)...
While LLMs show strong potential in supporting dental education through standardised exams, their performance varies by model and question type, and further improvements are needed to enhance reliability across different dental disciplines.
N. Acar, Fatih Sengul, Periş Çelikel et al.· European journal of dental e...· 0 citations
It is demonstrated that LLMs can serve as auxiliary tools in providing orthodontic patient information but responses should be checked by an expert before being presented to patients and should be adapted into simpler and more understandable language.
Alperen Erdoğan, Orhan Çiçek· Journal of International Den...· 0 citations
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