评估一个大型语言模型,用标准化框架将患者指令翻译成西班牙语
Mondira Ray1,2, Daniel J Kats1,2, Joss Moorkens3
1Division of General Pediatrics, Boston Children's Hospital, Boston, Massachusetts.
JAMA pediatrics
|July 7, 2025
概括
像GPT-4o这样的大型语言模型可以生成高质量的西班牙语患者指令,与人类翻译器相当. 这项技术可以改善对翻译材料的访问,并减少某些语言的工作量.
科学领域:
- 医疗信息学 医疗信息学
- 自然语言处理自然语言处理.
- 健康 公平 卫生 公平
背景情况:
- 英语水平有限的患者在获得关键的书面医疗信息方面面临重大障碍.
- 医疗保健中的有效沟通对于患者的安全和遵守治疗计划至关重要.
- 大型语言模型 (LLM) 为翻译患者材料提供了潜在的解决方案,但需要严格的验证.
研究的目的:
- 评估由GPT-4o生成的个性化儿科患者说明书的西班牙语翻译质量.
- 使用标准化框架,将GPT-4o的翻译质量与专业的人类翻译进行比较.
- 评估LLM在改善获得语言一致的医疗保健信息方面的潜力.
主要方法:
- 一项横截面研究,比较了GPT-4o和20个儿科患者说明书的专业人类翻译.
- 三位独立的医学翻译人员使用多维质量指标 (MQM) 框架对翻译进行了评估.
- 进行了同等性测试,以比较翻译质量得分.
主要成果:
- GPT-4o翻译的质量与人类翻译的质量相当,没有统计学上显著的差异 (平均差异为1.6MQM点).
- 在LLM产生更少的错误翻译错误.
- 在52%的案例中,专业翻译者更喜欢GPT-4o翻译.
结论:
- GPT-4o可以生成高质量的西班牙语患者说明书翻译,符合临床标准.
- 在减少翻译工作量方面,LLM显示出前景,可能为其他语言释放资源.
- 持续的人类监督是必不可少的,但LLMs可以提高医疗保健翻译的效率.
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