耦合词汇表与数据结构：来自LOINC的经验教训。
Coupling vocabularies and data structures: lessons from LOINC.
作者信息
Rocha R A, Huff S M
机构信息
Department of Medical Informatics, University of Utah School of Medicine, Salt Lake City, USA.
出版信息
Proc AMIA Annu Fall Symp. 1996:90-4.
Abstract
Using LOINC's data model for laboratory test result names as a starting point, an extended model is presented, coupled to a more complete vocabulary model. Justifications for this approach are obtained from a matching experiment that attempts to identify SNOMED terms that correspond to the various components of the LOINC names. Some limitations of LOINC's current vocabulary model, exposed during the matching process, are discussed.
摘要
以LOINC的实验室检测结果名称数据模型为出发点，提出了一个扩展模型，并与一个更完整的词汇模型相结合。这种方法的依据来自一项匹配实验，该实验试图识别与LOINC名称的各个组成部分相对应的SNOMED术语。文中讨论了在匹配过程中发现的LOINC当前词汇模型的一些局限性。
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