Large language models improve clinical decision making of medical students through patient simulation and structured feedback: a randomized controlled trial
The results suggest that AI-simulated medical history conversations can support CDM training, especially when combined with structured feedback. Such training format may serve as a cost-effective supplement to existing training methods, better preparing students for real medical history conversations.
Authors
- Dogus Darici (ORCID: https://orcid.org/0000-0002-2375-8792)
- Sarah Ricchizzi
- Max Hao Lu
- Marla J. Keller (ORCID: https://orcid.org/0000-0003-0417-4000)
- Walter Stummer (ORCID: https://orcid.org/0000-0002-3460-0640)
- Markus Holling (ORCID: https://orcid.org/0000-0002-2167-0789)
- Emilia Brügge
- Malin Arenbeck
- Lina Schur
Institutions
- University of Münster (DE)
- University Hospital Münster (DE)
- Einstein Center for Neurosciences Berlin (DE)
Publication Details
- Journal
- BMC Medical Education
- Published
- 2024-11-28
- DOI
- https://doi.org/10.1186/s12909-024-06399-7
- Citations
- 63
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 7.58
Funders
- Westfälische Wilhelms-Universität Münster