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Abstract

Purpose This study aims to explore the impact of AI on medical education by examining the relationship between AI use and academic performance in medical courses, evaluating the extent of its integration in students' clinical practice and application, and assessing how it enhances medical knowledge and understanding. In addition, the study measures medical students' attitudes toward the use of AI in their education and clinical training, providing a comprehensive overview of both its benefits and challenges.

Methods A cross-sectional survey was conducted between November 2024 and December 2024 with 168 participants, including students and interns from various academic years. The survey assessed AI's role in academic performance, education, and clinical practice. Statistical analyses, including factor and regression analyses, identified correlations and predictors of AI integration.

Results The analysis found that 85.6% of participants felt AI facilitated learning, 87.9% believed it improved understanding of complex topics, and 79.9% thought it enhanced academic performance. However, only 48.3% used AI for clinical decision-making, primarily for research and data analysis (79.2%), with just 12.5% using it for diagnostics. Additionally, 52% had never received AI training in clinical practice. Regression analysis revealed that AI experience significantly predicted positive perceptions and effective integration (p < 0.001).

Conclusion AI integration into medical education could revolutionize learning and clinical practice. However, the lack of structured AI training highlights a critical gap that must be addressed to prepare future healthcare professionals for an AI-driven medical field

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