ArticleImaging science in dentistry2024
Performance of ChatGPT 3.5 and 4 on U.S. dental examinations: the INBDE, ADAT, and DAT.
Article in Imaging science in dentistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.
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Who cites it
25 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Accuracy of Large Language Models in Answering Dental Examination Questions: A Systematic Review and Meta-Analysis.International dental journal · 2026Pooled it
- Can Large Language Models Serve as Reliable Tools for Information in Dentistry? A Systematic Review.International dental journal · 2025Pooled it
- Examining the Role of Artificial Intelligence in Assessment: A Comparative Study of ChatGPT and Educator-Generated Multiple-Choice Questions in a Dental Exam.European journal of dental education : official journal of the Association for Dental Education in Europe · 2026Article
- Guideline-based clinical reasoning in periodontology education: a comparative study of residents and large language models.BMC medical education · 2026Article
- Evaluation of ChatGPT-4o in oral and maxillofacial surgery examinations: a comparative study of performance on U.S. dental decks and chinese dental licensing examination practice questions.BMC oral health · 2026Article
- Comparison of the ChatGPT and deepseek models in responding to multiple choice questions related to rehabilitation of completely edentulous patients with complete dentures.BMC oral health · 2026Article
- Can artificial intelligence chatbots think like dentists? A comparative analysis based on dental specialty examination questions in restorative dentistry.BMC oral health · 2026Article
- A narrative discussion on the impact of respiratory infectious diseases on dental education in China: implications for curriculum design and student outcomes.Frontiers in dental medicine · 2026Review
- Large language models as data-driven engines for benchmarking preventive and clinical knowledge in Chinese dental examinations.Frontiers in oral health · 2026Article
- Diagnostic accuracy and repeatability of ChatGPT using textual and radiographic data in reversible pulpitis: a retrospective diagnostic study.Frontiers in bioinformatics · 2026Article
- Artificial intelligence-powered chatbots' responses to orthodontic questions from the dentistry specialization examination: Accuracy and source evaluation.Journal of dental sciences · 2026Article
- Analysis of multimodal large language models on visually-based questions in the Japanese National Examination for Dental Hygienists: A preliminary comparative study.Journal of dental sciences · 2026Article
- Applications and potential of ChatGPT in dentistry: Scoping review of research perspectives.Journal of dental sciences · 2026Review
- Performance comparison of large language models on pediatric dentistry questions in the Turkish dentistry specialization examination.BMC medical education · 2025Article
- Quantifying the speed-accuracy trade-off of large language models on oral and maxillofacial surgery multiple-choice questions.Scientific reports · 2025Article
- Evaluating and comparing student responses in examinations from the perspectives of human and artificial intelligence (GPT-4 and Gemini).BMC medical education · 2025Article
- Application of large language models in oral health education: a review of the literature.Canadian journal of dental hygiene : CJDH = Journal canadien de l'hygiene dentaire : JCHD · 2025Review
- Comparison of artificial intelligence systems in answering prosthodontics questions from the dental specialty exam in Turkey.Journal of dental sciences · 2025Article
- Comparing orthodontic pre-treatment information provided by large language models.BMC oral health · 2025Article
- Assessing ChatGPT-4's performance on the US prosthodontic exam: impact of fine-tuning and contextual prompting vs. base knowledge, a cross-sectional study.BMC medical education · 2025Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Recent advancements in artificial intelligence (AI), particularly tools such as ChatGPT developed by OpenAI, a U.S.-based AI research organization, have transformed the healthcare and education sectors. This study investigated the effectiveness of ChatGPT in answering dentistry exam questions, demonstrating its potential to enhance professional practice and patient care. Materials and Methods: This study assessed the performance of ChatGPT 3.5 and 4 on U.S. dental exams - specifically, the Integrated National Board Dental Examination (INBDE), Dental Admission Test (DAT), and Advanced Dental Admission Test (ADAT) - excluding image-based questions. Using customized prompts, ChatGPT's answers were evaluated against official answer sheets. Results: ChatGPT 3.5 and 4 were tested with 253 questions from the INBDE, ADAT, and DAT exams. For the INBDE, both versions achieved 80% accuracy in knowledge-based questions and 66-69% in case history questions. In ADAT, they scored 66-83% in knowledge-based and 76% in case history questions. ChatGPT 4 excelled on the DAT, with 94% accuracy in knowledge-based questions, 57% in mathematical analysis items, and 100% in comprehension questions, surpassing ChatGPT 3.5's rates of 83%, 31%, and 82%, respectively. The difference was significant for knowledge-based questions ( Conclusion: Both ChatGPT 3.5 and 4 effectively handled knowledge-based, case history, and comprehension questions, with ChatGPT 4 being more reliable and surpassing the performance of 3.5. ChatGPT 4's perfect score in comprehension questions underscores its trainability in specific subjects. However, both versions exhibited weaker performance in mathematical analysis, suggesting this as an area for improvement.
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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.