ArticleJournal of esthetic and restorative dentistry : official publication of the American Academy of Esthetic Dentistry ... [et al.]2025
Evaluating the Accuracy, Reliability, Consistency, and Readability of Different Large Language Models in Restorative Dentistry.
Article in Journal of esthetic and restorative dentistry : official publication of the American Academy of Esthetic Dentistry ... [et al.], 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- The Performance of Large Language Models on Antibiotic Prophylaxis for Endodontic Treatments.Australian endodontic journal : the journal of the Australian Society of Endodontology Inc · 2026Article
- Evaluation of the accuracy, quality, and readability of large language models on local anesthesia and general anesthesia-sedation in dentistry.BMC anesthesiology · 2026Article
- Errors in AI-Transformed Patient-Centered Mental Health Documentation Written by Psychiatrists: Qualitative Pre-Post Study.JMIR mental health · 2026Article
- Article
- Comparative assessment of quality, consistency, and reference accuracy of MIH-related clinical information generated by ChatGPT-4o and DeepSeek R1.BMC oral health · 2026Article
- Artificial intelligence chatbots versus dentists: a comparative knowledge assessment on traumatic dental injury management.BMC oral health · 2026Article
- Performance comparison of large language models on pediatric dentistry questions in the Turkish dentistry specialization examination.BMC medical education · 2025Article
- Comparative Evaluation of Responses from ChatGPT-5, Gemini 2.5 Flash, Grok 4, and Claude Sonnet-4 Chatbots to Questions About Endodontic Iatrogenic Events.Healthcare (Basel, Switzerland) · 2025Article
- Evaluation of Chatbot Responses to Text-Based Multiple-Choice Questions in Prosthodontic and Restorative Dentistry.Dentistry journal · 2025Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThis study aimed to evaluate the reliability, consistency, and readability of responses provided by various artificial intelligence (AI) programs to questions related to Restorative Dentistry. MATERIALS AND
methodsForty-five knowledge-based information and 20 questions (10 patient-related and 10 dentistry-specific) were posed to ChatGPT-3.5, ChatGPT-4, ChatGPT-4o, Chatsonic, Copilot, and Gemini Advanced chatbots. The DISCERN questionnaire was used to assess the reliability; Flesch Reading Ease and Flesch-Kincaid Grade Level scores were utilized to evaluate readability. Accuracy and consistency were determined based on the chatbots' responses to the knowledge-based questions.
resultsChatGPT-4, ChatGPT-4o, Chatsonic, and Copilot demonstrated "good" reliability, while ChatGPT-3.5 and Gemini Advanced showed "fair" reliability. Chatsonic exhibited the highest "DISCERN total score" for patient-related questions, while ChatGPT-4o performed best for dentistry-specific questions. No significant differences were found in readability among the chatbots (p > 0.05). ChatGPT-4o showed the highest accuracy (93.3%) for knowledge-based questions, while Copilot had the lowest (68.9%). ChatGPT-4 demonstrated the highest consistency between repetitions.
conclusionPerformance of AIs varied in terms of accuracy, reliability, consistency, and readability when responding to Restorative Dentistry questions. ChatGPT-4o and Chatsonic showed promising results for academic and patient education applications. However, the readability of responses was generally above recommended levels for patient education materials. CLINICAL SIGNIFICANCE: The utilization of AI has an increasing impact on various aspects of dentistry. Moreover, if the responses to patient-related and dentistry-specific questions in restorative dentistry prove to be reliable and comprehensible, this may yield promising outcomes for the future.
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