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Author Spotlight: Comprehensive Epigenetic Analysis for Investigating Human Cellular Plasticity and Environmental Adaptation Using Immunofluorescence Assays
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这就是SMART Text2FHIR管道.

Timothy A Miller1,2, Andrew J McMurry1,2, James Jones1,2

  • 1Boston Children's Hospital, Boston, MA.

AMIA ... Annual Symposium proceedings. AMIA Symposium
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PubMed
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此摘要是机器生成的。

一个新的开源工具,SMART Text2FHIR管道,将临床文本转换为快速医疗互操作资源 (FHIR). 这使得公共卫生和临床研究的无数据交换成为可能.

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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.
  • 临床数据的互操作性

背景情况:

  • 临床笔记包含有价值的非结构化数据.
  • 提取和结构化这些数据对于研究和公共卫生至关重要.
  • 现有的数据提取和互操作的方法可能是复杂和昂贵的.

研究的目的:

  • 开发一个开源,免费,易于部署的高吞吐量自然语言处理 (NLP) 模块.
  • 从临床笔记中提取概念.
  • 将这些概念映射到快速医疗互操作性资源 (FHIR).

主要方法:

  • 使用了Apache cTAKES,这是一个流行的开源NLP工具.
  • 开发了FHIR资源,用于否定和NLP采购的修饰器扩展.
  • 包含了概念来源的扩展.

主要成果:

  • 智能文本2FHIR管道是一个开源工具.
  • 它可以通过标准的包管理器和容器图像.
  • 能够有效地将临床文本转换为FHIR.

结论:

  • 智能Text2FHIR管道促进了数据流动性和数据传输的共同语言.
  • 该框架支持关键的公共卫生和临床研究用例.
  • 未来的工作包括扩大NLP概念映射和整合额外的NLP工具.