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使用GPT-4对IR程序报告的多语言简化评估

Hanzhou Hanssen Li¹, John T Moon¹, Sampath Kumar²

¹Division of Interventional Radiology and Image-Guided Medicine, Department of Radiology and Imaging Science, Emory University School of Medicine, Atlanta, Georgia.

Journal of vascular and interventional radiology : JVIR

|January 10, 2025

概括

像GPT-4这样的大型语言模型可以简化患者的复杂医疗报告. 这项技术提高了理解,并有助于翻译医学文本,提高了患者的沟通.

科学领域:

人工智能在医学中的应用
医疗信息学医疗信息学
自然语言处理自然语言处理.

背景情况:

干预放射学报告包含复杂的医学术语.
提高非专业人士对医疗报告的理解对于患者参与至关重要.
目前用于医学文本的翻译方法可能耗时且昂贵.

研究的目的:

评估使用GPT-4来总结干预放射学报告的可行性.
评估GPT-4总结对报告可读性和非专业人士理解性的影响.
为了确定GPT-4在将医疗报告翻译成多种语言的准确性.

主要方法:

GPT-4被用来总结200个干预放射学报告,分为8个类别.
使用弗莱什-金凯德阅读水平 (FKRL) 和弗莱什阅读易度得分 (FRES) 测量可读性.
摘要和翻译的准确性由干预放射科医生和双语放射科医生进行评估.

主要成果:

总结显著提高了可读性 (FKRL从10.7到7.0;FRES从41.9到73.0).
非专业人士的理解分数从2.5增加到5.0中的4.3.
翻译显示了轻微的错误信息,但没有关键错误;总结的准确性很高.

结论:

GPT-4有效地提高了干预放射学报告的可读性和理解性.
该研究表明,GPT-4有可能改善医疗保健中的患者-提供者沟通.
人工智能驱动的总结和翻译显示出更广泛的医学应用的前景.

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