Introduces a French OSCE dialogue dataset of 240 interactions and a modular LLM-based controllable virtual patient generation system with multi-level LLM-as-Judge evaluation for clinical skills training.
Kononowicz, Nabil Zary, Samuel Edelbring, Jorge Corral, and Inga Hege
3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 3verdicts
UNVERDICTED 3representative citing papers
An adaptive virtual patient uses a structural equation model fitted to nearly 2000 hours of real transcripts to dynamically update disclosure in response to therapist empathy and exploration, showing adaptation in a study with 20 clinicians across 80 sessions that outperforms prompt-only baselines.
CandorMD is a new AI simulation and feedback system for training clinicians in medical error disclosure, informed by interviews with physicians, risk managers, and experts.
citing papers explorer
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A French OSCE Dialogue Dataset and Controllable Virtual Patient System for Clinical Training
Introduces a French OSCE dialogue dataset of 240 interactions and a modular LLM-based controllable virtual patient generation system with multi-level LLM-as-Judge evaluation for clinical skills training.
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The Empirically Grounded Adaptive Virtual Patient for Psychotherapy Training: Disclosure That Responds to Therapist Micro-Skills
An adaptive virtual patient uses a structural equation model fitted to nearly 2000 hours of real transcripts to dynamically update disclosure in response to therapist empathy and exploration, showing adaptation in a study with 20 clinicians across 80 sessions that outperforms prompt-only baselines.
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CandorMD: An AI-Assisted Audio Simulation and Feedback System for Training Clinicians for Medical Error Disclosure
CandorMD is a new AI simulation and feedback system for training clinicians in medical error disclosure, informed by interviews with physicians, risk managers, and experts.