Structural group auditing of a UMLS semantic type's extent

Yan Chen, Huanying (Helen) Gu, Yehoshua Perl, James Geller, Michael Halper

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Each UMLS concept is assigned one or more of the semantic types (STs) from the Semantic Network. Due to the size and complexity of the UMLS, errors are unavoidable. We present two auditing methodologies for groups of semantically similar concepts. The straightforward procedure starts with the extent of an ST, which is the group of all concepts assigned this ST. We divide the extent into groups of concepts that have been assigned exactly the same set of STs. An algorithm finds subgroups of suspicious concepts. The human auditor is presented with these subgroups, which purportedly exhibit the same semantics, and thus she will notice different concepts with wrong or missing ST assignments. The dynamic procedure detects concepts which become suspicious in the course of the auditing process. Both procedures are applied to two semantic types. The results are compared with a comprehensive manual audit and show a very high error recall with a much higher precision.

Original languageEnglish (US)
Pages (from-to)41-52
Number of pages12
JournalJournal of Biomedical Informatics
Volume42
Issue number1
DOIs
StatePublished - Feb 2009

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Health Informatics

Keywords

  • Auditing
  • Group auditing
  • Partition
  • Refined semantic network
  • Refined semantic type
  • Semantic network
  • Semantic refinement
  • Semantic type assignment
  • Structural auditing
  • UMLS

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