Artificial Intelligence in Medicine
Volume 31, Issue 1 , Pages 29-44, May 2004

Auditing concept categorizations in the UMLS

  • Huanying (Helen) Gu

      Affiliations

    • Corresponding Author InformationCorresponding author. Tel.: +1-973-972-0995; fax: +1-973-972-8540.
    • Department of Health Informatics, University of Medicine and Dentistry of NJ, Newark, NJ 07107, USA
  • ,
  • Yehoshua Perl

      Affiliations

    • CS Department, New Jersey Institute of Technology, Newark, NJ 07102, USA
  • ,
  • Gai Elhanan

      Affiliations

    • Info-X Inc., Northvale, NJ 07647, USA
  • ,
  • Hua Min

      Affiliations

    • CS Department, New Jersey Institute of Technology, Newark, NJ 07102, USA
  • ,
  • Li Zhang

      Affiliations

    • CS Department, New Jersey Institute of Technology, Newark, NJ 07102, USA
  • ,
  • Yi Peng

      Affiliations

    • CS Department, New Jersey Institute of Technology, Newark, NJ 07102, USA

Received 18 March 2003; received in revised form 12 February 2004; accepted 27 February 2004.

Abstract 

The Unified Medical Language System (UMLS) integrates about 880,000 concepts from 100 biomedical terminologies. Each concept is categorized to at least one semantic type of the Semantic Network. During the integration, it is unavoidable that some categorization errors and inconsistencies will be introduced. In this paper, we present an auditing technique to find such errors and inconsistencies. Our technique is based on an expert reviewing the pure intersections of meta-semantic types of a metaschema, a compact abstract view of the UMLS Semantic Network. We use a divide and conquer approach, handling differently small pure intersections and medium to large pure intersections. By using this approach, we limit the number of concepts reviewed, for which we expect a high percentage of errors. We reviewed all concepts in 657 pure intersections containing one to 10 concepts. Various kinds of errors are identified and the analysis of the results are presented in the paper. Also, we checked the pure intersections containing more than 10 concepts for their semantic soundness, where the semantically suspicious pure intersections are presented in the paper and their concepts are reviewed.

Keywords:  Medical terminology, UMLS, Auditing, Metaschema, Semantic Network, Semantic type, Pure intersection, Categorization

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PII: S0933-3657(04)00038-7

doi:10.1016/j.artmed.2004.02.002

Artificial Intelligence in Medicine
Volume 31, Issue 1 , Pages 29-44, May 2004