Wei Duo, Wang Yue, Perl Yehoshua, Xu Junchuan, Halper Michael, Spackman Kent A
NJIT, Newark, NJ, USA.
AMIA Annu Symp Proc. 2008 Nov 6;2008:778-82.
SNOMED CT is an extensive terminology with an attendant amount of complexity. Two measures are proposed for quantifying that complexity. Both are based on abstraction networks, called the area taxonomy and the partial-area taxonomy, that provide, for example, distributions of the relationships within a SNOMED hierarchy. The complexity measures are employed specifically to track the complexity of versions of the Specimen hierarchy of SNOMED before and after it is put through an auditing process. The pre-audit and post-audit versions are compared. The results show that the auditing process indeed leads to a simplification of the terminology's structure.
SNOMED CT是一个庞大且伴随一定复杂性的术语集。本文提出了两种用于量化这种复杂性的方法。这两种方法均基于抽象网络，分别称为区域分类法和部分区域分类法，它们能够提供例如SNOMED层次结构中关系的分布情况。这些复杂性度量专门用于跟踪SNOMED标本层次结构在经过审核流程前后的版本复杂性。对审核前和审核后的版本进行了比较。结果表明，审核流程确实导致了术语结构的简化。
