AI-Enabled Medical Education: Current Insights and Future Prospects

Abstract

The rapid advancement of artificial intelligence (AI) is profoundly reshaping the landscape of medical education. Based on a review of recent research literature in the field of medical education, this paper systematically examines the current status, challenges, and future prospects of AI-enabled medical education. Currently, the application of AI in medical education has transitioned from conceptual exploration to widespread practice, primarily manifested in constructing personalized learning pathways, creating virtual simulation training environments, empowering intelligent teaching assistants, driving the reform of teaching evaluation, and facilitating the transformation of teachers' roles. These applications span numerous disciplines, including nursing, pharmacy, basic medicine, clinical medicine, and traditional Chinese medicine. However, its development also faces multiple challenges, including algorithmic opacity and data barriers, insufficient AI literacy among teachers and students, ethical and academic integrity risks, and obstacles to the deep integration of technology and education. Looking ahead, medical education will evolve towards a more personalized, intelligent, collaborative, and virtual-real integrated future. Constructing a new human-machine collaborative educational ecology, improving ethical norms and evaluation systems, and promoting the creative reconstruction of teachers' roles are key pathways to ensure that AI technology truly empowers medical education and cultivates outstanding medical talents.

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