医学
编码(集合论)
英语
急诊科
家庭医学
医学教育
护理部
计算机科学
程序设计语言
数学教育
数学
集合(抽象数据类型)
作者
Jesse Smith,Philip Choi,Paul Buntine
标识
DOI:10.1111/1742-6723.14280
摘要
Large language models (LLMs) have demonstrated mixed results in their ability to pass various specialist medical examination and their performance within the field of emergency medicine remains unknown.We explored the performance of three prevalent LLMs (OpenAI's GPT series, Google's Bard, and Microsoft's Bing Chat) on a practice ACEM primary examination.All LLMs achieved a passing score, with scores with GPT 4.0 outperforming the average candidate.Large language models, by passing the ACEM primary examination, show potential as tools for medical education and practice. However, limitations exist and are discussed.
科研通智能强力驱动
Strongly Powered by AbleSci AI