Large language models in trauma anesthesia education
Abstract
PURPOSE OF REVIEW: Large language model (LLM) use is rapidly growing among trainees and educators in clinical medicine, and new developments with LLM-augmented educational approaches have the potential to enhance learning and ease educator burden. We review LLM fundamentals, their use in clinical education, and how they may be integrated into trauma anesthesia education. RECENT FINDINGS: Traditional trauma anesthesia curricula and learning objectives lack granularity and the ability to meet unique learner needs. New approaches to clinical education and curriculum development are leveraging LLM capabilities, but applications for trauma anesthesia education remain insufficiently evaluated. SUMMARY: Augmenting traditional trauma anesthesia educational approaches with LLMs bears promise. Integrating numerous trauma anesthesia curricula and enhancing educational tools with LLMs to evaluate learner performance and satisfaction and educator burden would be informative to help refine best practices and target areas for improvement.
Fields of Study & Subjects
Artificial Intelligence in Healthcare and Education
Innovations in Medical Education
Artificial Intelligence in Education
Publication details
- Journal / source
- Current Opinion in Anaesthesiology
- Volume
- 39
- Issue
- 2
- Pages
- 160–166
- Publication date
- 17 February 2026
- Language
- EN