Mini Ruiz
Papers
3
Total Citations
67
H-Index
2
About
Mini Ruiz is a pioneering researcher at the intersection of medical education and artificial intelligence, specializing in the development of innovative virtual patient simulations to enhance clinical reasoning training. Her major contributions lie in integrating social robotics with large language models (LLMs) to create more interactive and authentic learning environments for health professions students. In her landmark 2025 mixed-methods study, she demonstrated how LLM-powered social robotic virtual patients can significantly improve clinical reasoning skills, garnering 37 citations for its groundbreaking approach. A subsequent qualitative comparison in rheumatology education (29 citations) further established the superiority of this modality over traditional computer-based virtual patients, highlighting its potential to transform medical training. Ruiz’s work addresses a critical gap in healthcare education, where inadequate clinical reasoning compromises patient safety. By combining cutting-edge robotics with advanced natural language processing, she has not only advanced pedagogical methods but also set a new standard for immersive, technology-driven learning. Her research is widely recognized for its practical impact, offering a scalable solution to train future clinicians in complex diagnostic decision-making.
Research Focus
Key Achievements
Top Papers
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