Literature DB >> 16929044

Auditing as part of the terminology design life cycle.

Hua Min1, Yehoshua Perl, Yan Chen, Michael Halper, James Geller, Yue Wang.   

Abstract

OBJECTIVE: To develop and test an auditing methodology for detecting errors in medical terminologies satisfying systematic inheritance. This methodology is based on various abstraction taxonomies that provide high-level views of a terminology and highlight potentially erroneous concepts.
DESIGN: Our auditing methodology is based on dividing concepts of a terminology into smaller, more manageable units. First, we divide the terminology's concepts into areas according to their relationships/roles. Then each multi-rooted area is further divided into partial-areas (p-areas) that are singly-rooted. Each p-area contains a set of structurally and semantically uniform concepts. Two kinds of abstraction networks, called the area taxonomy and p-area taxonomy, are derived. These taxonomies form the basis for the auditing approach. Taxonomies tend to highlight potentially erroneous concepts in areas and p-areas. Human reviewers can focus their auditing efforts on the limited number of problematic concepts following two hypotheses on the probable concentration of errors.
RESULTS: A sample of the area taxonomy and p-area taxonomy for the Biological Process (BP) hierarchy of the National Cancer Institute Thesaurus (NCIT) was derived from the application of our methodology to its concepts. These views led to the detection of a number of different kinds of errors that are reported, and to confirmation of the hypotheses on error concentration in this hierarchy.
CONCLUSION: Our auditing methodology based on area and p-area taxonomies is an efficient tool for detecting errors in terminologies satisfying systematic inheritance of roles, and thus facilitates their maintenance. This methodology concentrates a domain expert's manual review on portions of the concepts with a high likelihood of errors.

Entities:  

Mesh:

Year:  2006        PMID: 16929044      PMCID: PMC1656963          DOI: 10.1197/jamia.M2036

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


  26 in total

1.  Benefits of an object-oriented database representation for controlled medical terminologies.

Authors:  H Gu; M Halper; J Geller; Y Perl
Journal:  J Am Med Inform Assoc       Date:  1999 Jul-Aug       Impact factor: 4.497

2.  Discovering missed synonymy in a large concept-oriented Metathesaurus.

Authors:  W T Hole; S Srinivasan
Journal:  Proc AMIA Symp       Date:  2000

3.  Partitioning an object-oriented terminology schema.

Authors:  H Gu; Y Perl; M Halper; J Geller; F Kuo; J J Cimino
Journal:  Methods Inf Med       Date:  2001-07       Impact factor: 2.176

4.  The cohesive metaschema: a higher-level abstraction of the UMLS Semantic Network.

Authors:  Yehoshua Perl; Zong Chen; Michael Halper; James Geller; Li Zhang; Yi Peng
Journal:  J Biomed Inform       Date:  2002-06       Impact factor: 6.317

5.  Auditing the UMLS for redundant classifications.

Authors:  Yi Peng; Michael H Halper; Yehoshua Perl; James Geller
Journal:  Proc AMIA Symp       Date:  2002

6.  The Unified Medical Language System (UMLS): integrating biomedical terminology.

Authors:  Olivier Bodenreider
Journal:  Nucleic Acids Res       Date:  2004-01-01       Impact factor: 16.971

7.  Auditing concept categorizations in the UMLS.

Authors:  Huanying Gu; Yehoshua Perl; Gai Elhanan; Hua Min; Li Zhang; Yi Peng
Journal:  Artif Intell Med       Date:  2004-05       Impact factor: 5.326

8.  A terminological and ontological analysis of the NCI Thesaurus.

Authors:  W Ceusters; B Smith; L Goldberg
Journal:  Methods Inf Med       Date:  2005       Impact factor: 2.176

9.  The Unified Medical Language System.

Authors:  D A Lindberg; B L Humphreys; A T McCray
Journal:  Methods Inf Med       Date:  1993-08       Impact factor: 2.176

10.  Designing a controlled medical vocabulary server: the VOSER project.

Authors:  R A Rocha; S M Huff; P J Haug; H R Warner
Journal:  Comput Biomed Res       Date:  1994-12
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  54 in total

1.  Auditing consistency and usefulness of LOINC use among three large institutions - using version spaces for grouping LOINC codes.

Authors:  M C Lin; D J Vreeman; Clement J McDonald; S M Huff
Journal:  J Biomed Inform       Date:  2012-01-28       Impact factor: 6.317

2.  Analysis of a study of the users, uses, and future agenda of the UMLS.

Authors:  Yan Chen; Yehoshua Perl; James Geller; James J Cimino
Journal:  J Am Med Inform Assoc       Date:  2007-01-09       Impact factor: 4.497

3.  Analysis of error concentrations in SNOMED.

Authors:  Michael Halper; Yue Wang; Hua Min; Yan Chen; George Hripcsak; Yehoshua Perl; Kent A Spackman
Journal:  AMIA Annu Symp Proc       Date:  2007-10-11

Review 4.  A review of auditing methods applied to the content of controlled biomedical terminologies.

Authors:  Xinxin Zhu; Jung-Wei Fan; David M Baorto; Chunhua Weng; James J Cimino
Journal:  J Biomed Inform       Date:  2009-03-12       Impact factor: 6.317

5.  Auditing complex concepts in overlapping subsets of SNOMED.

Authors:  Yue Wang; Duo Wei; Junchuan Xu; Gai Elhanan; Yehoshua Perl; Michael Halper; Yan Chen; Kent A Spackman; George Hripcsak
Journal:  AMIA Annu Symp Proc       Date:  2008-11-06

6.  Complexity measures to track the evolution of a SNOMED hierarchy.

Authors:  Duo Wei; Yue Wang; Yehoshua Perl; Junchuan Xu; Michael Halper; Kent A Spackman; Kent Spackman
Journal:  AMIA Annu Symp Proc       Date:  2008-11-06

7.  Validating UMLS Semantic Type Assignments Using SNOMED CT Semantic Tags.

Authors:  Huanying Gu; Zhe He; Duo Wei; Gai Elhanan; Yan Chen
Journal:  Methods Inf Med       Date:  2018-04-05       Impact factor: 2.176

8.  Quality assurance of chemical ingredient classification for the National Drug File - Reference Terminology.

Authors:  Ling Zheng; Hasan Yumak; Ling Chen; Christopher Ochs; James Geller; Joan Kapusnik-Uner; Yehoshua Perl
Journal:  J Biomed Inform       Date:  2017-07-16       Impact factor: 6.317

Review 9.  Introducing the Big Knowledge to Use (BK2U) challenge.

Authors:  Yehoshua Perl; James Geller; Michael Halper; Christopher Ochs; Ling Zheng; Joan Kapusnik-Uner
Journal:  Ann N Y Acad Sci       Date:  2016-10-17       Impact factor: 5.691

10.  Structural group-based auditing of missing hierarchical relationships in UMLS.

Authors:  Yan Chen; Huanying Helen Gu; Yehoshua Perl; James Geller
Journal:  J Biomed Inform       Date:  2008-08-20       Impact factor: 6.317

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