Jianwen Zeng
Papers
1
Total Citations
11
H-Index
1
About
Dr. Jianwen Zeng is a pioneering researcher at the intersection of artificial intelligence and medical education, with a primary focus on leveraging large language models (LLMs) to transform clinical training. Their most cited work, "Embracing the Future of Medical Education With Large Language Model–Based Virtual Patients: Scoping Review" (2025, 11 citations), systematically analyzes the emerging applications of LLM-driven virtual patients for simulation-based learning. Dr. Zeng’s major contribution lies in mapping the current landscape of this nascent field—identifying key use cases, technological challenges, and pedagogical opportunities—thereby providing a foundational framework for future research. By synthesizing evidence on how LLMs can create more realistic, adaptive, and scalable patient interactions, their work directly addresses critical gaps in medical education, such as the need for cost-effective, repeatable clinical scenarios. This scoping review has quickly become a reference point for educators and technologists seeking to integrate AI into curricula. Dr. Zeng’s research not only highlights the transformative potential of LLMs but also sets the stage for rigorous evaluation of their effectiveness, marking them as a key voice shaping the future of healthcare training.
Research Focus
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Top Papers
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