Digital and Intelligence Education in Medicine: A Bibliometric and Visualization Analysis Using CiteSpace and VOSviewer

Abstract

This study provides a comprehensive bibliometric analysis of the development and current status of digital and intelligence education in medicine over the past decade, with a focus on the integration of digital technologies in professional training. Using bibliometric methods, we analyzed publications between 2015 and 2024, identifying key research themes, emerging technologies, and the contributions of leading institutions and countries. The results show a steady increase in publications, particularly from 2022 to 2024, reflecting a growing global interest in digital and intelligence education in medicine, driven by technological advancements and the COVID-19 pandemic. Key themes identified include artificial intelligence-powered personalization, virtual reality in training, deep learning for medical imaging, and the use of language models for interactive teaching. However, challenges such as disparities in global research capacity, data privacy concerns, ethical issues, and resource inequality are also highlighted. Notably, the integration of intelligent digital platforms in education has been found to be transformative, particularly in clinical training, adaptive learning, and medical diagnostics simulation. The study concludes that while digital and intelligent technologies have the potential to revolutionize medical education, addressing ethical, technical, and resource-based challenges is crucial for equitable global implementation. Future research should focus on fostering international collaboration, developing standardized frameworks, and creating inclusive, low-cost digital tools to democratize medical education, thereby improving healthcare outcomes worldwide.

Graphical abstract

Keywords

digital technologies / artificial intelligence / medical education / bibliometrics / CiteSpace / New Medicine

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Acknowledgments

This study was funded by the Teaching Reform Research Project of the Medical School of Wuhan University (Grant No. 2024ZD29) and the Comprehensive Reform Project for Undergraduate Education Quality Construction at Wuhan University (Digital and Intelligence Education in Health and Medicine).

Conflict of Interest

The authors declare that they have no conflict of interest.

Data Availability Statements

The authors confirm that all data generated or analyzed during this study are included in this published article.

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