Viking Huss
Papers
3
Total Citations
67
H-Index
2
About
Viking Huss is a pioneering researcher at the intersection of medical education and artificial intelligence, whose work is reshaping how future clinicians develop critical diagnostic skills. His primary research focuses on leveraging social robotics and large language models (LLMs) to create immersive virtual patient simulations for clinical reasoning training. Huss’s landmark 2025 mixed-methods study, which has garnered 37 citations, demonstrated how combining humanoid robots with LLMs can significantly enhance the authenticity and interactivity of clinical encounters compared to traditional computer-based simulations. His 2024 qualitative comparison within rheumatology (29 citations) further established that LLM-powered robotic virtual patients better engage medical students in differential diagnosis and decision-making processes. By addressing the well-documented gap in clinical reasoning competence that compromises patient safety, Huss’s work provides scalable, high-fidelity training tools that bridge simulation and real-world practice. His innovative approach has positioned him as a leading voice in technology-enhanced medical pedagogy, with ongoing contributions that promise to transform how healthcare professionals develop the nuanced reasoning skills essential for quality patient care.
Research Focus
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Top Papers
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