Large language models for generating medical examinations: systematic review.

ABSTRACT:

Background

Writing multiple choice questions (MCQs) for the purpose of medical exams is challenging. It requires extensive medical knowledge, time and effort from medical educators. This systematic review focuses on the application of large language models (LLMs) in generating medical MCQs.

Methods

The authors searched for studies published up to November 2023. Search terms focused on LLMs generated MCQs for medical examinations. Non-English, out of year range and studies not focusing on AI generated multiple-choice questions were excluded. MEDLINE was used as a search database. Risk of bias was evaluated using a tailored QUADAS-2 tool.

Results

Overall, eight studies published between April 2023 and October 2023 were included. Six studies used Chat-GPT 3.5, while two

SUBMITTER: Artsi Y 

PROVIDER: S-EPMC10981304 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature