使用LOINC和WHO-FIC术语映射原则对Pomeranian健康研究数据进行语义丰富
Esther Thea Inau1, Dörte Radke2, Linda Bird3
1Department of Medical Informatics, University Medicine Greifswald, Greifswald, Germany.
JAMIA open
|March 10, 2025
概括
这项研究成功地将98.6%的SHIP实验室数据字典代码映射到LOINC,提高了人口健康研究的数据公正性和互操作性.
科学领域:
- 生物医学信息学 生物医学信息学
- 数据管理管理数据管理.
- 人口健康研究 人口健康研究
背景情况:
- 波默兰的健康研究 (SHIP) 需要语义上丰富的实验室数据,以便更好地管理数据.
- 遵守FAIR原则 (可查找,可访问,可互操作,可重复使用) 对于基于人口的队列研究至关重要.
- 标准化实验室数据字典可以增强数据的整合和分析.
研究的目的:
- 用逻辑观测标识符名称和代码 (LOINC) 来语义丰富SHIP实验室数据字典.
- 为了改善对SHIP队列研究的FAIR数据管理原则的遵守.
- 提高实验室数据的互操作性和可重复使用性.
主要方法:
- 从SHIP-START-4实验室数据字典的代码映射到LOINC代码.
- 遵循世界卫生组织国际分类家族 (WHO-FIC) 网络术语映射原则.
- 使用了一种旨在用于术语映射和语义丰富的工作流.
主要成果:
- 在SHIP-START-4实验室数据字典中的72个 (98.6%) 源代码中成功注释了71个LOINC代码.
- 实现了32个一对一 (1:1) 映射和39个复杂映射.
- 所有成功的映射均为等值 (=) 匹配,确保语义一致性.
结论:
- 用LOINC代码对SHIP实验室数据词典的语义丰富提高了数据互操作性和公平性.
- 映射过程有助于更好的语义数据检索和集成.
- 建议包括合作,未来的队列研究数据词典的前性注释,以提高标准化.
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