Landscape and Trends in the Application of Artificial Intelligence in Medical Education

Abstract

This paper addresses the knowledge gap in the field of artificial intelligence applications in medical education by conducting comprehensive visual analyses using data from the Web of Science (WoS) database spanning the past decade. The study investigates the current landscape, research trends, and emerging areas within this domain. Our findings reveal that prominent research focuses within artificial intelligence in medical education encompass robot-assisted surgical training, intelligent assessment feedback systems, and smart virtual simulation systems. The evolution of research in this field is observed to transition from standardization to personalization, from the physical to virtual-real integration, and from an emphasis on independent thinking to fostering human-machine collaboration. These results provide valuable insights for researchers in the artificial intelligence and medical education communities. In conclusion, this research contributes to a better understanding of the dynamics and trends within the application of artificial intelligence in medical education and sets the stage for further exploration and innovation in the field. Future work may involve exploring the specific impacts of these technologies on medical training and patient outcomes, as well as the development of advanced AI-based educational tools.

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