ArticleJournal of the American Medical Informatics Association : JAMIA2024
Benchmarking the symptom-checking capabilities of ChatGPT for a broad range of diseases.
Article in Journal of the American Medical Informatics Association : JAMIA, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Optimizing prompting strategies improves large language model classification of pain- and fatigue-related functional impact in childhood cancer survivors.Communications medicine · 2026Article
- Comparison of Emotional Content in Text Responses From Physicians and AI Chatbots to Patient Health Queries: Cross-Sectional Study.Journal of medical Internet research · 2026Article
- Evaluating the accuracy of ChatGPT model versions for giving care-seeking advice.Communications medicine · 2026Article
- A Survey on Medical Competence Evaluation Benchmarks for Large Language Models.Health care science · 2026Review
- Evolution of AI in anatomy education study based on comparison of current large language models against historical ChatGPT performance.Scientific reports · 2025Article
- Large Language Model Symptom Identification From Clinical Text: Multicenter Study.Journal of medical Internet research · 2025Article
- Development of Lung Cancer Risk Prediction Machine Learning Models for Equitable Learning Health System: Retrospective Study.JMIR AI · 2024Article
- A GPT-based EHR modeling system for unsupervised novel disease detection.Journal of biomedical informatics · 2024Article
- Large language models in biomedicine and health: current research landscape and future directions.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- A publishing infrastructure for Artificial Intelligence (AI)-assisted academic authoring.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Optimizing GPT-4 Turbo Diagnostic Accuracy in Neuroradiology through Prompt Engineering and Confidence Thresholds.Diagnostics (Basel, Switzerland) · 2024Article
- Longitudinal Changes in Diagnostic Accuracy of a Differential Diagnosis List Developed by an AI-Based Symptom Checker: Retrospective Observational Study.JMIR formative research · 2024Article
- Enhancing AI Chatbot Responses in Health Care: The SMART Prompt Structure in Head and Neck Surgery.OTO openArticle
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThis study evaluates ChatGPT's symptom-checking accuracy across a broad range of diseases using the Mayo Clinic Symptom Checker patient service as a benchmark.
methodsWe prompted ChatGPT with symptoms of 194 distinct diseases. By comparing its predictions with expectations, we calculated a relative comparative score (RCS) to gauge accuracy.
resultsChatGPT's GPT-4 model achieved an average RCS of 78.8%, outperforming the GPT-3.5-turbo by 10.5%. Some specialties scored above 90%. DISCUSSION: The test set, although extensive, was not exhaustive. Future studies should include a more comprehensive disease spectrum.
conclusionChatGPT exhibits high accuracy in symptom checking for a broad range of diseases, showcasing its potential as a medical training tool in learning health systems to enhance care quality and address health disparities.
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Registered trials
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