Large language models for generating key-feature questions in medical education.

ABSTRACT: In this study, we conducted a descriptive study to evaluate the quality of KFQs generated by OpenAI's o3 model. We developed a reusable generic prompt for KFQ generation, designed in alignment with the Medical Council of Canada's KFQ development guidelines. We also created an evaluation metric to systematically assess the quality of the KFQs based on the KFQ development guideline. Twenty unique cardiology-focused KFQs were created using recent European Society of Cardiology guidelines as reference. Each KFQ was independently assessed by two cardiology experts using the quality checklist, with disagreements resolved by a third reviewer. Descriptive statistics were used to summarize checklist compliance and final acceptability ratings. Of the 20 KFQs, 3 (15%) were rated 'Accept as is' and 17

SUBMITTER: Kıyak YS 

PROVIDER: S-EPMC12573569 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature