New abstraction networks and a new visualization tool in support of auditing the SNOMED CT content.

James Geller, Christopher Ochs, Yehoshua Perl, Junchuan Xu

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

Medical terminologies are large and complex. Frequently, errors are hidden in this complexity. Our objective is to find such errors, which can be aided by deriving abstraction networks from a large terminology. Abstraction networks preserve important features but eliminate many minor details, which are often not useful for identifying errors. Providing visualizations for such abstraction networks aids auditors by allowing them to quickly focus on elements of interest within a terminology. Previously we introduced area taxonomies and partial area taxonomies for SNOMED CT. In this paper, two advanced, novel kinds of abstraction networks, the relationship-constrained partial area subtaxonomy and the root-constrained partial area subtaxonomy are defined and their benefits are demonstrated. We also describe BLUSNO, an innovative software tool for quickly generating and visualizing these SNOMED CT abstraction networks. BLUSNO is a dynamic, interactive system that provides quick access to well organized information about SNOMED CT.

Original languageEnglish (US)
Pages (from-to)237-246
Number of pages10
JournalUnknown Journal
Volume2012
StatePublished - 2012

All Science Journal Classification (ASJC) codes

  • Medicine(all)

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