ArticleJournal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine2025
Artificial intelligence in sleep medicine: assessing the diagnostic precision of ChatGPT-4.
Article in Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed.
- Interobserver Agreement Between Artificial Intelligence, Radiologist, and Gynecologist in Hysterosalpingography Interpretation: A Retrospective Comparative Study.Diagnostics (Basel, Switzerland) · 2026Article
- Performance of nine large language models on real-world polysomnography interpretation for obstructive sleep apnea: a multi-dimensional comparative analysis.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 · 2026Article
- Diagnostic accuracy of multimodal large language models in differentiating epileptic from functional seizures in smartphone recorded videos.Scientific reports · 2026Article
- Performance of successive generative pretrained transformers (GPT) models in medical cases and board style questions.Scientific reports · 2026Article
- Assessment of frontier Large Language Models in sleep medicine.Frontiers in digital health · 2026Article
- Performance of large language models on sleep medicine certification examination: a comprehensive multi-model analysis.Frontiers in medicine · 2026Article
- Large language model derived regular expressions for sleep phenotyping from electronic health record: a feasibility study.Sleep advances : a journal of the Sleep Research Society · 2026Article
- Artificial intelligence may fill the gap of underdiagnosis in sleep medicine: the role of ChatGPT-4.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2025Article
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2 authors.
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Abstract
STUDY
objectivesLarge language models such as ChatGPT-4 are emerging in medicine, including sleep medicine, where artificial intelligence is used to analyze sleep data and predict treatment outcomes. Effectiveness of large language models in accurately diagnosing sleep disorders based on clinical history has not yet been studied. This study evaluates ChatGPT-4's diagnostic performance using clinical vignettes.
methodsNineteen clinical vignettes containing patient history, physical examination findings, and diagnostic tests from the
resultsThe mean accuracy for differential diagnoses was 63.27% ± 15.61% (standard deviation), ranging from 33.33-100%. The mean number of artificial intelligence-generated differential diagnoses matching the American Academy of Sleep Medicine case differential diagnoses was 2.79 ± 0.71 (standard deviation). For final diagnoses, ChatGPT-4 scored a total of 30 out of a possible 38, resulting in an overall accuracy of 78.95%. The model achieved a mean score of 1.58 ± 0.61 (standard deviation) out of 2, with 68.42% of cases achieving a full match. Performance was higher in cases with fewer differential diagnoses, whereas accuracy decreased in complex cases.
conclusionsChatGPT-4 demonstrates promising diagnostic potential in sleep medicine, with moderate to high accuracy in identifying differential and final diagnoses, although its variability in more complex cases calls for refinement and clinical validation. CITATION: Patel A, Cheung J. Artificial intelligence in sleep medicine: assessing the diagnostic precision of ChatGPT-4.
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