ArticleBMC oral health2025
Can deepseek and ChatGPT be used in the diagnosis of oral pathologies?
Article in BMC oral health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.
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Who cites it
42 citing papers in PubMed.
- Comparative Benchmark of Seven Large Language Models for Traumatic Dental Injury Knowledge.European journal of dentistry · 2026Article
- Agreement in Staging and Treatment Recommendations Among Clinicians, Text-Only Clinicians, DeepSeek-V3, and ChatGPT-4o for Nasopharyngeal Carcinoma Patients.Cancer medicine · 2026Article
- Evaluation of large language models in root resorption scenarios: an ESE-aligned comparative performance assessment.Odontology · 2026Article
- Context-Guided Mixture-of-Experts with Multimodal LLMs for Lesion Detection in Buccal Mucosa Images.International dental journal · 2026Article
- Performance Comparison of a Domain-Specific Chatbot and General-Purpose Chatbots in Dental Traumatology.Dental traumatology : official publication of International Association for Dental Traumatology · 2026Article
- A Guideline-Concordant Chatbot Framework for Structured Colorectal Cancer Screening: Multistage Feasibility Study.Journal of medical Internet research · 2026Article
- A comparative evaluation of large language models in diagnosis and treatment planning in restorative dentistry.BMC oral health · 2026Article
- ChatGPT-5 vs oral medicine experts for rank-based differential diagnosis of oral lesions: a prospective, biopsy-validated comparison.Odontology · 2026Article
- JADE: jawbone lesion diagnosis and decision supporting system.Dento maxillo facial radiology · 2026Article
- Can artificial intelligence applications be utilised in the management of dental trauma? A comparison of ChatGPT, Gemini, and DeepSeek.BMC oral health · 2026Article
- Applications of DeepSeek in Medicine: Bibliometric Analysis and Scoping Review.Journal of medical Internet research · 2026Article
- Article
- Evaluation of the accuracy, quality, and readability of large language models on local anesthesia and general anesthesia-sedation in dentistry.BMC anesthesiology · 2026Article
- Comparison of the diagnostic accuracy of dentists and ChatGPT in jawbone lesions.BMC oral health · 2026Article
- Article
- Article
- Accuracy of AI Tools in the Diagnosis of Benign, Potentially Malignant and Malignant Oral Lesions: A Pilot Study.Journal of clinical medicine · 2026Article
- Comparative performance of large language models for patient-oriented support in dental trauma emergencies.BMC oral health · 2026Article
- Comparative assessment of quality, consistency, and reference accuracy of MIH-related clinical information generated by ChatGPT-4o and DeepSeek R1.BMC oral health · 2026Article
- Performance of five large language models in oral and maxillofacial surgery exam questions: a comparative study.BMC oral health · 2026Article
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2 authors.
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Abstract
objectiveArtificial intelligence (AI) has been widely used in various medical fields to support diagnostic development. The development of different AI techniques has made important contributions to early diagnoses. This research compares and evaluates the diagnostic accuracy of ChatGPT-4o and Deepseek-v3 AI applications in 16 clinical case scenarios in oral pathologies. METHODOLOGY: Clinical case scenarios of 16 imaginary oral pathologies were prepared by the authors. The cases were asked to provide 3 possible preliminary diagnoses to two different AI applications, DeepSeek-V3 and ChatGPT-4o, and to reference the literature for these diagnoses. The diagnoses of both AI applications were evaluated with Likert scale by 20 different specialists from two different specialties.
resultsThe mean score for DeepSeek-v3 was 4.02 ± 0.36. For ChatGPT-4o it was 3.15 ± 0.41. According to the average scores, both models performed at a moderate to high level. Also, between the two AI models. DeepSeek-v3 was statistically better in 9 out of 16 clinical scenarios, while ChatGPT-4o was statistically better in 1 question. In general, DeepSeek-v3 was statistically more successful in the comparison of the two models (p = 0.024). In terms of references, ChatGPT-4o showed 62 references and 50 of them were fake, while 8 out of 48 references were fake in DeepSeek-v3.
conclusionsChatbot applications have the potential to become a valuable consultant for clinicians in the future thanks to its fast-processing ability. It is clear that it can help healthcare services by reducing the workload of clinicians. It can be said that the Deepseek-v3 model produces better results compared to ChatGPT-4o, but both applications need to be improved for routine use. It is thought that the release of versions of AI models that can only perform scans in the medical field and respond to clinicians by providing more reliable resources may make these models more valuable.
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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.