ArticleClinical rheumatology2025
Assessment of ChatGPT's adherence to EULAR diagnostic criteria and therapeutic protocols for rheumatoid arthritis at two distinct time points, 14 days apart, utilizing binary and multiple-choice inquiries.
Article in Clinical rheumatology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Automating the triage of rheumatology outpatient referrals: a comparative evaluation of 23 large language models under simple and advanced prompting.Rheumatology international · 2026Article
- Moderate-to-substantial agreement of ChatGPT-5 for Kellgren-Lawrence grading on synthetic knee radiographs: a controlled cross-sectional observer agreement study.Rheumatology international · 2026Article
- Gut Instincts, Machine Decisions: Evaluating AI Accuracy in the Diagnosis and Treatment of Disorders of Gut-Brain Interaction.Neurogastroenterology and motility · 2026Article
- Artificial intelligence in rheumatology: a cross-sectional Scopus-based analysis.Rheumatology international · 2026Article
- Evaluation of ChatGPT-4o and Gemini for gout management: a comparative analysis based on EULAR guidelines.Scientific reports · 2026Article
- Comparison of artificial intelligence and rheumatologists in nailfold capillaroscopic evaluation.Revista da Associacao Medica Brasileira (1992) · 2026Article
- Evaluation of artificial ıntelligence use in ankylosing spondylitis with ChatGPT-4: patient and physician perspectives.Clinical rheumatology · 2025Article
- Comparative evaluation of ChatGPT and LLaMA for reliability, quality, and accuracy in familial Mediterranean fever.European journal of pediatrics · 2025Article
- Assessing Chat Generative Pretrained Transformer-4's clinical utility in acute compartment syndrome: a comprehensive evaluation of accuracy, completeness, and readability.Revista da Associacao Medica Brasileira (1992) · 2025Article
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Abstract
objectivesArtificial intelligence (AI) possesses considerable promise in healthcare to offer decision help in particular domains, including rheumatoid arthritis (RA). This study assesses the adherence of the advanced AI model ChatGPT-v4 to the European League Against Rheumatism (EULAR) recommendations.
methodsThe research employed a 100-item questionnaire consisting of true/false and multiple-choice formats, accompanied with real-world clinical scenarios developed concurrently with EULAR in the therapy of RA. Inquiries addressed diagnostic criteria, therapeutic alternatives, and follow-up procedures. Two rheumatologists assessed the ChatGPT for accuracy, consistency, and comprehensiveness utilizing a 6-point Likert scale.
resultsEvaluation occurred at baseline and on day 14. AI rectified the majority of errors at baseline in the paired questions. It did not advance on specific responses. One of the two previously incongruent responses remained unaltered, while the other was rectified. The 48 originally congruent responses rose to 49 on day 14. In binary questions, AI exhibited greater coherence than in multiple-choice questions. At baseline, 43 (86%) of the multiple-choice items were answered correctly. Upon reevaluation, 42 (84%) were found to be accurate. One response was erroneous on day 14. Three of the seven initially erroneous responses remained unaltered. Four erroneous responses were later rectified.
conclusionChatGPT demonstrated efficacy in addressing binary and multiple-choice questions formulated according to EULAR guidelines for RA. The findings validated that AI can serve as a clinical support instrument in RA. It demonstrated that AI can be enhanced. AI attained accuracy in objective information and promptly rectified the error. Key Points • AI in healthcare: The integration of artificial intelligence, specifically ChatGPT-v4, in clinical practice aims to enhance decision-making in RA by adhering to EULAR recommendations for diagnosis, treatment, and follow-up. • Inter-rater reliability: High agreement levels were noted among the evaluators, with Cohen's kappa coefficients of 0.92 for binary questions and 0.94 for multiple-choice questions. • AI learning dynamics: The study reveals that ChatGPT showed improvement in understanding and answering more complex questions over time, unlike findings in previous studies where AI struggled with consistency. • Implications for clinical practice: The findings support the growing role of AI as a reliable tool in rheumatology, suggesting potential for personalized, evidence-based patient care.
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