Chaoqun Dong
Papers
1
Total Citations
11
H-Index
1
About
Chaoqun Dong is an emerging researcher at the intersection of artificial intelligence and medical education, with a focused interest in leveraging large language models (LLMs) to transform clinical training methodologies. His most notable work, a 2025 scoping review titled "Embracing the Future of Medical Education With Large Language Model–Based Virtual Patients," has already garnered 11 citations within its first year of publication — a strong indicator of its relevance and timeliness in a rapidly evolving field. In this study, Dong systematically examines how LLM-powered virtual patients are being developed and deployed in medical education settings, mapping the current landscape of applications and identifying future research directions. His scholarship addresses a critical gap in healthcare training: the need for scalable, realistic, and accessible patient simulation tools that can supplement or enhance traditional clinical exposure. By situating cutting-edge AI technology within the practical demands of medical curricula, Dong's research speaks to educators, technologists, and clinicians alike. His work positions him as a thoughtful contributor to the growing conversation around responsible and effective AI integration in health professions education.
Research Focus
Key Achievements
Top Papers
- 1