Complexity measures to track the evolution of a SNOMED hierarchy.

Duo Wei, Yue Wang, Yehoshua Perl, Junchuan Xu, Michael Halper, Kent A. Spackman

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)778-782
Number of pages5
JournalAMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
StatePublished - 2008

All Science Journal Classification (ASJC) codes

  • Medicine(all)

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