AI-Assisted Medical Education and Training: Technological Applications, Effectiveness Evaluation, and Ethical Considerations

Abstract

This review explores AI’s role in medical education and training, covering its applications, effectiveness, ethical considerations, and future directions. In applications, AI enhances diverse training areas: AI-powered simulations (with AR/VR) enable safe surgical practice, offering video labeling and automated feedback (e.g., in robotic surgery); diagnostic training tools use ML to simulate clinical cases and provide instant feedback (though unregulated use risks academic integrity); personalized learning platforms tailor content to students’ needs, with 88% of students viewing AI as a key learning aid; AI aids medical image analysis training (e.g., via 3D Slicer) to build anatomy knowledge; and virtual patients simulate clinical conversations, helping develop communication skills (e.g., for nursing students). Effectiveness evaluation shows mixed but promising results: Most students/educators (91.11%) believe AI boosts knowledge acquisition; AI chatbots increase learning interest (though not always clinical reasoning); AI tools enhance learning efficiency and engagement, yet comparisons with traditional methods vary—some find no NBME score differences, while over-reliance may harm problem-solving. Long-term impacts on professionals’ performance need more study. Ethical challenges include data privacy risks (requiring encryption/anonymization), algorithm bias (needing diverse training data), the necessity of human oversight (to address fairness/explainability), potential threats to doctor-patient empathy (though VR can sometimes foster empathy), and ensuring equitable access (via open-source tools/subsidies). Future directions involve integrating AI with VR/AR for immersive training, developing adaptive learning systems, and researching the optimal AI-human interaction balance. AI holds great promise for cultivating skilled, ethical medical professionals, pending responsible implementation.

Keywords

artificial intelligence / medical education / technological applications / medical ethics

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