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This paper is in the following e-collection/theme issue:

Development and Evaluation of Research Methods, Instruments and Tools (1441) e-Learning and Digital Medical Education (1655) Research Instruments, Questionnaires, and Tools (1242) Testing and Assessment in Medical Education (244) Artificial Intelligence (AI) in Medical Education (871) AI Language Models in Health Care (839)

Published on in Vol 10 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/84904, first published .
AI vs. human expert: Robot head, doctor, and scales of justice with AI and EXPERT books.

Fine-Tuned Large Language Models for Generating Multiple-Choice Questions in Anesthesiology: Psychometric Comparison With Faculty-Written Items

Fine-Tuned Large Language Models for Generating Multiple-Choice Questions in Anesthesiology: Psychometric Comparison With Faculty-Written Items

Authors of this article:

Carlos Ramon Hölzing1 Author Orcid Image ;   Charlotte Meynhardt1 Author Orcid Image ;   Patrick Meybohm1 Author Orcid Image ;   Sarah König2 Author Orcid Image ;   Peter Kranke1 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

Journals

  1. Banerjee S, Agarwal M. The Pocket Tutor - Generating Competency-Based Clinical Vignettes with Artificial Intelligence for Medical Postgraduate Competitive Exam Preparation. Galore International Journal of Health Sciences and Research 2026:69 View
  2. Damor P, Gill S, Wani W, Arora G, Charan M. A Psychometric Comparison of Faculty-Authored and Large Language Model-Generated Multiple-Choice Questions in Endodontics. Cureus 2026 View
  3. Li C, Wang W, Li C, Wang X, Ma X, Zhao W, Xie Y, Wang W, Lin R, Su Z, Wei M. Leveraging large language models to generate multiple-choice questions for epilepsy education. Frontiers in Medicine 2026;13 View