ArticleKorean journal of orthodontics2025
Artificial intelligence solutions for temporomandibular joint disorders: Contributions and future potential of ChatGPT.
Article in Korean journal of orthodontics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Temporomandibular Disorders Diagnosis: Current Challenges and the Promising Role of Artificial Intelligence.European journal of dentistry · 2026Article
- Accuracy and empathy of AI-based conversational chatbots in response to temporomandibular dysfunction related queries.PEC innovation · 2026Article
- A bilingual evaluation of chatbot performance in bruxism-related information: accuracy and readability across two models.BMC oral health · 2026Article
- Domain-Specific vs. General-Purpose Large Language Models in Orthodontics: A Blinded Comparison of AlimGPT, GPT-4o, Gemini, and Llama.Dentistry journal · 2026Article
- Comparative evaluation of ChatGPT, Gemini, and Grok in clinical decision-making and general knowledge assessment for impacted maxillary canines.Korean journal of orthodontics · 2026Article
- Evaluating chat generative pre-trained transformer responses to common patient questions on temporomandibular disorders.Revista da Associacao Medica Brasileira (1992) · 2026Article
- Performance of ChatGPT-4o, Gemini Advanced-2.0, and DeepSeek-V3 in the diagnosis and management of temporomandibular disorders.BMC oral health · 2025Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: This study aimed to evaluate the reliability and usefulness of information generated by Chat Generative Pre-Trained Transformer (ChatGPT) on temporomandibular joint disorders (TMD). Methods: We asked ChatGPT about the diseases specified in the TMD classification and scored the responses using Likert reliability and usefulness scales, the modified DISCERN (mDISCERN) scale, and the Global Quality Scale (GQS). Results: The highest Likert scores for both reliability and usefulness were for masticatory muscle disorders (mean ± standard deviation [SD]: 6.0 ± 0), and the lowest scores were for inflammatory disorders of the temporomandibular joint (mean ± SD: 4.3 ± 0.6 for reliability, 4.0 ± 0 for usefulness). The median Likert reliability score indicates that the responses are highly reliable. The median Likert usefulness score was 5 (4-6), indicating that the responses were moderately useful. A comparative analysis was performed, and no statistically significant differences were found in any subject for either reliability or usefulness ( Conclusions: Although ChatGPT-4 has significant potential, it can be used as an additional source of information regarding TMD for patients and clinicians.
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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.