医学
背景(考古学)
自然语言处理
胸片
领域(数学分析)
注释
射线照相术
人工智能
放射科
计算机科学
古生物学
数学分析
数学
生物
作者
Cody Savage,Hyoungsun Park,Kijung Kwak,Andrew D. Smith,Steven Rothenberg,Vishwa S. Parekh,Florence X. Doo,Paul H. Yi
出处
期刊:American Journal of Roentgenology
[American Roentgen Ray Society]
日期:2024-01-17
卷期号:222 (4)
被引量:3
摘要
GPT-4 outperformed a radiology domain-specific natural language processing model in classifying imaging findings from chest radiograph reports, both with and without predefined labels. Prompt engineering for context further improved performance. The findings indicate a role for large language models to accelerate artificial intelligence model development in radiology by automating data annotation.
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