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There are various healthcare agencies in the United States—some of which are managed by religious institutions and others by different government branches.
Parish nursing is a growing specialty nursing profession that focuses on holistic healthcare, health promotion, and illness prevention. It blends professional nursing practice with a health ministry, focusing on health and healing within the context of a Christian community. Parish nurses serve as health educators, referral sources,...
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xMEN:用于跨语言医疗实体规范化的模块化工具包.

Florian Borchert1, Ignacio Llorca1, Roland Roller2

  • 1Hasso Plattner Institute for Digital Engineering, University of Potsdam, Potsdam 14482, Germany.

JAMIA open
|December 30, 2024
PubMed
概括

xMEN系统增强了跨语言的医疗实体规范化,特别是在低资源语言中. 它通过利用多语言别名和新的培训技术来提高绩效,实现了最先进的结果.

关键词:
简称CTCT,即阴影式的CT.统一的医疗语言系统临床自然语言处理 临床自然语言处理链接实体链接实体多语言的多语种.

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科学领域:

  • 自然语言处理自然语言处理.
  • 计算语言学 计算语言学
  • 生物信息学是一种生物信息学.

背景情况:

  • 医疗实体规范化对于医疗保健中的信息提取至关重要.
  • 现有系统经常因有限的术语和注释而与低资源语言扎.
  • 提高跨语言能力对于全球健康信息学至关重要.

研究的目的:

  • 开发一个强大的跨语言医疗实体规范化 (MEN) 系统,在高资源和低资源的场景中表现良好.
  • 通过利用多语言信息来解决语言特定资源的稀缺问题.
  • 引入新的培训方法,并在跨语言背景下重新排名医疗实体.

主要方法:

  • 提出了xMEN,一个模块化系统,用于跨语言的MEN.
  • 雇佣了使用多语言别名的跨语言候选人.
  • 整合了一个可训练的交叉编码器 (CE) 用于候选人排名,具有新的排名规范化术语.
  • 开发了弱标记的数据集,用于在低资源场景中使用机器翻译和注释投影进行重新排名.

主要成果:

  • xMEN 在几个欧洲语言的基准数据集上实现了最先进的性能.
  • 在缺乏目标任务培训数据的场景中,证明了监督较弱的CE的有效性.
  • 识别了复杂的实体,作为正常化的一个剩余挑战.

结论:

  • xMEN 提供了强大的性能,用于跨多种语言的医疗实体规范化,即使具有有限的标记数据和术语.
  • 该系统的模块化设计允许轻松集成新的模块和数据集.
  • 发布了一个开源的Python工具包,以促进可重现的研究和未来的基准.