在部署纯功能时使用HL7 FHIR RDF资源来丰富知识图的患者数据的原型ETL管道
Adeel Ansari1, Marisa Conte2, Allen Flynn2
1Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, 250 College St., Toronto, ON, M5T 1R8, Canada. adeel.ansari@camh.ca.
Journal of biomedical semantics
|August 31, 2025
概括
一个新的数据管道使用纯函数来丰富患者的知识图. 这有助于在临床研究中实现透明,基于标准的数据处理.
科学领域:
- 生物医学信息学
- 数据科学
- 临床研究信息学
背景情况:
- 知识图 (KG) 对于临床护理和研究具有价值.
- 用患者数据丰富基因组需要系统和透明的方法.
- 利用现有的实体学和数据标准促进语义互操作性.
研究的目的:
- 开发和测试一种用于KG丰富的新型数据处理管道.
- 使新患者的特征能够被计算和整合到现有的KG中.
- 展示使用基于标准的透明数据处理方法.
主要方法:
- 开发了一个数据处理管道来提取,计算和返回新的患者特征.
- 使用电子健康记录和患者调查数据.
- 员工健康7级的FHIR RDF数据表示和验证标准.
主要成果:
- 成功实施并测试了丰富患者KG的管道.
- 证明了FHIR规定的RDF数据资源类型的程序验证.
- 展示了该管道能够代表患者层面的新特征.
结论:
- 基于标准的语义数据处理管道可以增强知识图技术.
- 纯功能可以被部署和追踪以获得新的患者特征.
- 语义数据处理管道有助于通过链接元数据对新患者计算进行报告.
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