Akademik Veri Yönetim Sistemi
Journal of Clinical Medicine, cilt.14, sa.5, 2025 (SCI-Expanded)
Background: Sarcopenia, an age-related decline in muscle mass and function, poses significant health risks. While AI tools like ChatGPT-4 (ChatGPT-4o) are increasingly used in healthcare, their accuracy in addressing sarcopenia remains unclear. Methods: ChatGPT-4’s responses to 20 frequently asked sarcopenia-related questions were evaluated by 34 experts using a four-criterion scale (relevance, accuracy, clarity, Ccmpleteness). Responses were rated from 1 (low) to 5 (high), and interrater reliability was assessed via intraclass correlation coefficient (ICC). Results: ChatGPT-4 received consistently high median scores (5.0), with ≥90% of evaluators rating responses ≥4. Relevance had the highest mean score (4.7 ± 0.5), followed by accuracy (4.6 ± 0.6), clarity (4.6 ± 0.6), and completeness (4.6 ± 0.7). ICC analysis showed poor agreement (0.416), with Completeness displaying moderate agreement (0.569). Conclusions: ChatGPT-4 provides highly relevant and structured responses but with variability in accuracy and clarity. While it shows potential for patient education, expert oversight remains essential to ensure clinical validity. Future studies should explore patient-specific data integration and AI comparisons to refine its role in sarcopenia management.