Elkin P L, Brown S H
Laboratory of Biomedical Informatics, Department of Internal Medicine, Mayo Medical School, Mayo Foundation, Baldwin 4B, Mayo Clinic, 200 First Street S.W., Rochester, MN 55905-0002, USA.
J Biomed Inform. 2002 Oct-Dec;35(5-6):281-8. doi: 10.1016/s1532-0464(03)00019-4.
Compositional (post-coordinated) terminologies are one potential solution to the problem of content completeness. However, they have the potential to render data incomparable. For computers to determine that compositional expressions are comparable, the relations between the composed components that are understood implicitly by human readers must be represented explicitly for computer manipulation. We discuss a technique for discovering and formalizing the implicit semantic relationships in two vocabularies: the International Classification of Disease Version 9 Clinical Modification (ICD9-CM), and SNOMED-Reference Terminology (SNOMED-RT). The results of this technique are used to augment the existing SNOMED-RT relation ontology, which is a necessary step in automated concept mapping between systems. The reference terminology must contain all the semantics implicit in the classification in order to map concepts between the two representations. We also provide an explicit representation of the implied semantics of ICD9-CM. This tabulation will be useful for other knowledge engineering efforts involving ICD9-CM.
组合式(后协调)术语是解决内容完整性问题的一种潜在方案。然而,它们有可能使数据无法进行比较。要让计算机确定组合式表达式具有可比性,就必须将人类读者隐含理解的组合成分之间的关系明确表示出来,以便计算机进行处理。我们讨论了一种用于发现和形式化两种词汇表中隐含语义关系的技术:《国际疾病分类第九版临床修订本》(ICD9-CM)和医学系统命名法参考术语集(SNOMED-RT)。该技术的结果用于扩充现有的SNOMED-RT关系本体,这是系统之间自动概念映射的必要步骤。参考术语必须包含分类中隐含的所有语义,以便在两种表示形式之间映射概念。我们还提供了ICD9-CM隐含语义的显式表示。这种列表对于涉及ICD9-CM的其他知识工程工作将很有用。