ArticleJournal of medical Internet research2024
AI in Dental Radiology-Improving the Efficiency of Reporting With ChatGPT: Comparative Study.
Article in Journal of medical Internet research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 3 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Effectiveness, Safety, and Workflow Burden of Large Language Model-Based Medical Report Generation: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Educational Applications of ChatGPT in University-Based Dental Education. A Systematic Review.European journal of dental education : official journal of the Association for Dental Education in Europe · 2026Pooled it
- The performance of large language models in dentomaxillofacial radiology: a systematic review.Dento maxillo facial radiology · 2025Pooled it
- Improving patient communication and understanding of medical reports through text simplification with ChatGPT: a comparative study.Oral and maxillofacial surgery · 2026Article
- Comparison of Multimodal Large Language Models and Oral and Maxillofacial Radiologists in the Detection of Incidental Findings on Panoramic Radiographs: A CBCT-Referenced Diagnostic Accuracy Study.Healthcare (Basel, Switzerland) · 2026Article
- For the record: a narrative review of ambient voice technology in clinical documentation for dentistry and wider healthcare.British dental journal · 2026Review
- Diagnostic accuracy of ChatGPT-5 in evaluating root canal treatment and periapical pathosis on periapical radiographs.Restorative dentistry & endodontics · 2026Article
- Comparative Evaluation of Large Language Models for Reporting Jaw Lesions on Panoramic Radiographs.Diagnostics (Basel, Switzerland) · 2026Article
- AI-based diagnostic evaluation of GPT-4o for crown-fracture detection on maxillary periapical radiographs: effects of prompt detail and customization.BMC oral health · 2026Article
- Multidimensional Evaluation of AI-Generated Patient Information on Cone Beam-Computed Tomography.Journal of imaging informatics in medicine · 2026Article
- A systematic review of the limitations of large language models in generating healthcare content.PLOS digital health · 2026Article
- Measuring the Impact of AI on Report-Drafting Efficiency in Chest Computed Tomography Interpretation: Retrospective Analysis.Journal of medical Internet research · 2026Article
- Evaluation of ChatGPT's ability to detect intraosseous pathologies with panoramic radiographs.BMC oral health · 2026Article
- Artificial Intelligence Versus Human Dental Expertise in Diagnosing Periapical Pathosis on Periapical Radiographs: A Multicenter Study.Bioengineering (Basel, Switzerland) · 2026Article
- Artificial intelligence applications in automated dental report generation - a scoping review.Frontiers in oral health · 2026Review
- Diagnostic accuracy and repeatability of ChatGPT using textual and radiographic data in reversible pulpitis: a retrospective diagnostic study.Frontiers in bioinformatics · 2026Article
- Application of artificial intelligence in oral health management: challenges and opportunities.Frontiers in medicine · 2026Review
- Educational aspects of artificial intelligence in oral and maxillofacial radiology: insights from a scoping review.BMC medical education · 2025Article
- Performance comparison of large language models on pediatric dentistry questions in the Turkish dentistry specialization examination.BMC medical education · 2025Article
- The reliability of answers from four different AI chatbots on periodontology theoretical exam questions: an evaluation in dental education.BMC oral health · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundStructured and standardized documentation is critical for accurately recording diagnostic findings, treatment plans, and patient progress in health care. Manual documentation can be labor-intensive and error-prone, especially under time constraints, prompting interest in the potential of artificial intelligence (AI) to automate and optimize these processes, particularly in medical documentation.
objectiveThis study aimed to assess the effectiveness of ChatGPT (OpenAI) in generating radiology reports from dental panoramic radiographs, comparing the performance of AI-generated reports with those manually created by dental students.
methodsA total of 100 dental students were tasked with analyzing panoramic radiographs and generating radiology reports manually or assisted by ChatGPT using a standardized prompt derived from a diagnostic checklist.
resultsReports generated by ChatGPT showed a high degree of textual similarity to reference reports; however, they often lacked critical diagnostic information typically included in reports authored by students. Despite this, the AI-generated reports were consistent in being error-free and matched the readability of student-generated reports.
conclusionsThe findings from this study suggest that ChatGPT has considerable potential for generating radiology reports, although it currently faces challenges in accuracy and reliability. This underscores the need for further refinement in the AI's prompt design and the development of robust validation mechanisms to enhance its use in clinical settings.
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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.