CHAT GPT VS. RHEUMATOLOGISTS: DO WE STILL NEED THE CLINICIAN?

Objectives: Artificial intelligence (AI) encompasses systems designed to perform tasks that require human cognitive abilities, such as reasoning, decision-making, and problem-solving. Open AI’s Generative Pre-Trained Transformer (GPT) model family, including ChatGPT, is widely recognized for its ability to generate human-like text and facilitate interactive discussions. ChatGPT has potential applications in diagnosis assistance and medical education in healthcare, yet its adoption raises concerns. Our study aims to evaluate ChatGPT’s diagnostic performance in identifying autoinflammatory diseases compared to clinicians, exploring its potential as an accessible tool for physicians and patients. Material and Methods: We evaluated the diagnostic performance of a publicly accessible AI model against two clinicians for identifying familial Mediterranean fever (FMF) and periodic fever, aphthous stomatitis, pharyngitis, and adenitis syndrome (PFAPA). Clinical data from 50 patients were presented anonymously in structured format to both the AI model and the clinicians. Diagnoses were compared to confirmed clinical diagnoses. Results: A total of 50 patients were included in the study. The AI model suggested a rheumatologic diagnosis in 94% of cases but correctly diagnosed only 50% of them. In comparison, clinicians made accurate diagnoses in 76% and 70% of cases, respectively. Conclusion: The development of AI has attracted significant attention in healthcare, as it has in other fields. However, AIgenerated data may be incorrect, highlighting the importance of expert supervision. AI should complement, not replace physicians, enhancing their capabilities. Future research should evaluate AI performance across different fields and its impact on decision-making to ensure reliable use through standardized guidelines.