背景:医学术语和代码系统,在健康领域发挥着至关重要的作用,很少是静态的,但随着知识和术语的发展而发生变化。这包括添加,删除和重新标记术语,and,如果术语是分层组织的,改变他们的立场。如果使用相同术语的多个版本并且需要互操作性,则跟踪这些改变可能变得重要。
方法:我们提出了一种用于术语版本之间自动更改跟踪的新方法。它由声明性导入管道组成,将源术语转换为通用数据模型。然后,我们使用语义和词汇变化检测算法。它们产生基于本体的术语更改表示,可以使用语义查询语言进行查询。
结果:该方法在检测添加剂方面被证明是准确的,删除,术语的重新定位和重命名。在版本间术语映射信息由发布者提供的情况下,我们能够高度增强区分简单添加/删除和细化/合并术语的能力。
结论:如果术语细化和合并是相关的,则该方法对于半自动变更处理是有效的,如果有其他映射信息可用,则该方法对于自动变更检测是有效的。
BACKGROUND: Medical terminologies and code systems, which play a vital role in the health domain, are rarely static but undergo changes as knowledge and terminology evolves. This includes addition, deletion and relabeling of terms, and, if terms are organized hierarchically, changing their position. Tracking these changes may become important if one uses multiple versions of the same terminology and interoperability is desired.
METHODS: We propose a new method for automatic change tracking between terminology versions. It consists of a declarative import pipeline, which translates source terminologies into a common data model. We then use semantic and lexical change detection algorithms. They produce an ontology-based representation of terminology changes, which can be queried using semantic query languages.
RESULTS: The method proves accurate in detecting additions, deletions, relocations and renaming of terms. In cases where inter-version term mapping information is provided by the publisher, we were able to highly enhance the ability to differentiate between simple additions/deletions and refinements/consolidation of terms.
CONCLUSIONS: The method proves effective for semi-automatic change handling if term refinements and consolidation are relevant and for automatic change detection if additional mapping information is available.