Suppr超能文献

利用扩展语义关系建立生物医学元数据注册库的语义互操作性。

Establishing semantic interoperability of biomedical metadata registries using extended semantic relationships.

作者信息

Park Yu Rang, Yoon Young Jo, Kim Hye Hyeon, Kim Ju Han

机构信息

Seoul National University Biomedical Informatics (SNUBI), Division of Biomedical Informatics.

出版信息

Stud Health Technol Inform. 2013;192:618-21.

Abstract

Achieving semantic interoperability is critical for biomedical data sharing between individuals, organizations and systems. The ISO/IEC 11179 MetaData Registry (MDR) standard has been recognized as one of the solutions for this purpose. The standard model, however, is limited. Representing concepts consist of two or more values, for instance, are not allowed including blood pressure with systolic and diastolic values. We addressed the structural limitations of ISO/IEC 11179 by an integrated metadata object model in our previous research. In the present study, we introduce semantic extensions for the model by defining three new types of semantic relationships; dependency, composite and variable relationships. To evaluate our extensions in a real world setting, we measured the efficiency of metadata reduction by means of mapping to existing others. We extracted metadata from the College of American Pathologist Cancer Protocols and then evaluated our extensions. With no semantic loss, one third of the extracted metadata could be successfully eliminated, suggesting better strategy for implementing clinical MDRs with improved efficiency and utility.

摘要

实现语义互操作性对于个人、组织和系统之间的生物医学数据共享至关重要。ISO/IEC 11179元数据注册(MDR)标准已被视为实现此目的的解决方案之一。然而,该标准模型存在局限性。例如,不允许表示由两个或更多值组成的概念,包括具有收缩压和舒张压值的血压。在我们之前的研究中,我们通过一个集成的元数据对象模型解决了ISO/IEC 11179的结构局限性。在本研究中,我们通过定义三种新的语义关系(依赖关系、组合关系和变量关系)为该模型引入语义扩展。为了在实际环境中评估我们的扩展,我们通过映射到现有的其他元数据来测量元数据减少的效率。我们从美国病理学家学会癌症协议中提取了元数据,然后对我们的扩展进行了评估。在没有语义损失的情况下,三分之一的提取元数据可以成功消除,这表明在提高效率和实用性的情况下,实施临床MDR有更好的策略。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验