Large language models in trauma anesthesia education

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Authors: David W. Corpman, Elodie Lang, Tyler J. Law
Cited by: 0
References: 20

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