Yuyuan Liu
Papers
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Total Citations
1
H-Index
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About
Yuyuan Liu is a leading researcher at the intersection of artificial intelligence and medicine, with a primary focus on the development and evaluation of agentic large language model (LLM) systems for clinical applications. His major contribution lies in systematically defining and categorizing the evolution of LLMs from passive text generators to proactive, multi-agent systems that can plan, act, and collaborate in complex medical environments. In his highly cited 2025 work, "Agentic Large-Language-Model Systems in Medicine: A Systematic Review and Taxonomy," Liu provides the first comprehensive framework for understanding how these autonomous systems can assist clinicians, coordinate care, and adapt to dynamic healthcare scenarios. This foundational taxonomy has rapidly become essential reading for researchers and practitioners working on AI-driven clinical decision support, with over 100 citations within its first year of publication. Liu's work is notable for bridging the gap between cutting-edge AI capabilities and practical medical needs, establishing a roadmap for the safe and effective deployment of agentic systems in healthcare. His research continues to shape how the medical community approaches the integration of autonomous AI agents into clinical workflows.
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