AI BASED ORTHOPAEDIC EDUCATION - AN EDGE OVER CONVENTIONAL EDUCATION. MULTICENTRE COMPARATIVE COHORT STUDY

Background: Orthopedic education has traditionally relied on the Gurukul system, emphasizing hands-on training, mentorship, and didactic lectures. However, the integration of artificial intelligence (AI) is transforming this educational model. AI-driven learning offers personalized training, real-time feedback, predictive analytics, and immersive simulations. This study evaluates the impact of AI-based orthopedic education on learning outcomes, resident satisfaction, teacher involvement, and research productivity. Methods: A three-year study was conducted on 500 orthopedic residents worldwide, divided equally into traditional and AI-based education groups. Satisfaction scores, research publications, and test performance were compared. Statistical analyses included paired t-tests, chi-square tests, Pearson correlation, regression analysis, and ANOVA with a significance threshold of p<0.05. AI-based educational models from five countries—AI-enabled cadaver simulation (United States), smart orthopedic training platform (India), predictive surgical outcome simulator (Germany), robot-assisted training modules (Japan), and virtual reality surgical labs (Australia)—were evaluated for their effectiveness. Results: Residents trained with AI-based methods reported significantly higher satisfaction scores (85%) compared to those in traditional education (70%). Teachers also demonstrated improved engagement (90% vs. 75%). AI-trained residents achieved 1.8 times higher publication rates and performed 15% better on test scores. Statistical analysis confirmed a strong correlation between resident and teacher satisfaction (r=0.85, p<0.05). AI-based training improved surgical precision by 25%, reduced errors by 20-30%, and enhanced research productivity. Conclusion: AI-based orthopedic education significantly enhances learning outcomes, resident and teacher satisfaction, and research productivity. AI-driven simulation, predictive analytics, and adaptive learning platforms offer an effective complement to traditional training. While AI integration presents challenges such as data quality and curriculum adaptation, its potential to revolutionize orthopedic education is evident. Future research should focus on scalable AI solutions and long-term impacts on medical training.