ArticleDiagnostics (Basel, Switzerland)2024
The Role of Large Language Models (LLMs) in Providing Triage for Maxillofacial Trauma Cases: A Preliminary Study.
Article in Diagnostics (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled it.
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Who cites it
21 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Testing and evaluation of generative large language models in electronic health record applications: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2026Pooled it
- Can Large Language Models Serve as Reliable Tools for Information in Dentistry? A Systematic Review.International dental journal · 2025Pooled it
- Multimodal Deep Learning Based on Ultrasound Images and Clinical Data for Better Ovarian Cancer Diagnosis.Journal of imaging informatics in medicine · 2026Article
- Article
- Diagnosis and Triage Performance of Contemporary Large Language Models on Short Clinical Vignettes.Journal of medical systems · 2025Article
- Evaluating the Efficacy of Large Language Models in Generating Medical Documentation: A Comparative Study of ChatGPT-4, ChatGPT-4o, and Claude.Aesthetic plastic surgery · 2025Article
- ChatGPT in Oral Pathology: Bright Promise or Diagnostic Mirage.Medicina (Kaunas, Lithuania) · 2025Article
- Artificial intelligence in maxillofacial trauma: expert ally or unreliable assistant?Medicina oral, patologia oral y cirugia bucal · 2025Article
- Large language models for structured reporting in radiology: past, present, and future.European radiology · 2025Review
- Translation and Validation of the Gothenburg Trismus Questionnaire-2 into Italian Language.Journal of clinical medicine · 2025Article
- Authorship transparency and equity in otolaryngology and maxillofacial surgery: current practices and the potential impact of large language models.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2025Article
- Management of Dupuytren's Disease: A Multi-Centric Comparative Analysis Between Experienced Hand Surgeons Versus Artificial Intelligence.Diagnostics (Basel, Switzerland) · 2025Article
- Chat Generative Pre-Trained Transformer (ChatGPT) in Oral and Maxillofacial Surgery: A Narrative Review on Its Research Applications and Limitations.Journal of clinical medicine · 2025Review
- Evolutionary patterns and research frontiers of artificial intelligence in age-related macular degeneration: a bibliometric analysis.Quantitative imaging in medicine and surgery · 2025Article
- Decoding wisdom: Evaluating ChatGPT's accuracy and reproducibility in analyzing orthopantomographic images for third molar assessment.Computational and structural biotechnology journal · 2025Article
- Artificial Intelligence in Audiology: A Scoping Review of Current Applications and Future Directions.Sensors (Basel, Switzerland) · 2024Article
- Article
- Large language model triaging of simulated nephrology patient inbox messages.Frontiers in artificial intelligence · 2024Article
- Assessing the role of advanced artificial intelligence as a tool in multidisciplinary tumor board decision-making for recurrent/metastatic head and neck cancer cases - the first study on ChatGPT 4o and a comparison to ChatGPT 4.0.Frontiers in oncology · 2024Article
- Evaluating the Efficacy of Large Language Models for Dizzy History Taking and Peripheral Vestibular Disorder Diagnosis.Journal of otolaryngology - head & neck surgery = Le Journal d'oto-rhino-laryngologie et de chirurgie cervico-facialeArticle
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn the evolving field of maxillofacial surgery, integrating advanced technologies like Large Language Models (LLMs) into medical practices, especially for trauma triage, presents a promising yet largely unexplored potential. This study aimed to evaluate the feasibility of using LLMs for triaging complex maxillofacial trauma cases by comparing their performance against the expertise of a tertiary referral center.
methodsUtilizing a comprehensive review of patient records in a tertiary referral center over a year-long period, standardized prompts detailing patient demographics, injury characteristics, and medical histories were created. These prompts were used to assess the triage suggestions of ChatGPT 4.0 and Google GEMINI against the center's recommendations, supplemented by evaluating the AI's performance using the QAMAI and AIPI questionnaires.
resultsThe results in 10 cases of major maxillofacial trauma indicated moderate agreement rates between LLM recommendations and the referral center, with some variances in the suggestion of appropriate examinations (70% ChatGPT and 50% GEMINI) and treatment plans (60% ChatGPT and 45% GEMINI). Notably, the study found no statistically significant differences in several areas of the questionnaires, except in the diagnosis accuracy (GEMINI: 3.30, ChatGPT: 2.30;
conclusionsThis exploratory investigation underscores the potential of LLMs in enhancing clinical decision making for maxillofacial trauma cases, indicating a need for further research to refine their application in healthcare settings.
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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.