Artificial Intelligence in Clinical Medical Training: Current Applications and Future Directions

DOI: https://doi.org/10.62517/jmpe.202618107

Author(s)

Weiyun Bi, Lang Li

Affiliation(s)

Clinical Skills Training Center, Xijing Hospital, Air Force Medical University, Xi’an, China

Abstract

Artificial intelligence (AI) technologies are profoundly transforming contemporary clinical medical education, catalyzing a paradigm shift from traditional experience-based instruction to precise, personalized and immersive learning. This paper systematically examines key application scenarios and representative practices of AI in clinical training, highlights major challenges, and outlines future development directions. The analysis underscores three principal domains in which AI advances clinical education: virtual patient and clinical environment simulations, personalized adaptive learning pathways, and the modeling of clinical reasoning and decision-making. Evidence demonstrates that AI-driven tools can significantly enhance the efficiency and quality of medical training. Nevertheless, critical barriers including algorithmic transparency, data privacy protection and ethical governance-continue to hinder large-scale adoption. In the foreseeable future, the deep integration of AI into clinical medical training depends on standardized curricula, innovative simulation technologies, and robust ethical frameworks, which together will foster clinical competencies aligned with the evolving demands of intelligent healthcare.

Keywords

Artificial Intelligence; Clinical Medical Training; Virtual Patients; Personalized Learning; Medical Education Ethics

References

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