Abstraction of complex concepts with a refined partial-area taxonomy of SNOMED

Document Type

Article

Publication Date

2-1-2012

Abstract

An algorithmically-derived abstraction network, called the partial-area taxonomy, for a SNOMED hierarchy has led to the identification of concepts considered complex. The designation " complex" is arrived at automatically on the basis of structural analyses of overlap among the constituent concept groups of the partial-area taxonomy. Such complex concepts, called overlapping concepts, constitute a tangled portion of a hierarchy and can be obstacles to users trying to gain an understanding of the hierarchy's content. A new methodology for partitioning the entire collection of overlapping concepts into singly-rooted groups, that are more manageable to work with and comprehend, is presented. Different kinds of overlapping concepts with varying degrees of complexity are identified. This leads to an abstract model of the overlapping concepts called the disjoint partial-area taxonomy, which serves as a vehicle for enhanced, high-level display. The methodology is demonstrated with an application to SNOMED's Specimen hierarchy. Overall, the resulting disjoint partial-area taxonomy offers a refined view of the hierarchy's structural organization and conceptual content that can aid users, such as maintenance personnel, working with SNOMED. The utility of the disjoint partial-area taxonomy as the basis for a SNOMED auditing regimen is presented in a companion paper. © 2011 Elsevier Inc.

Identifier

84856391399 (Scopus)

Publication Title

Journal of Biomedical Informatics

External Full Text Location

https://doi.org/10.1016/j.jbi.2011.08.013

ISSN

15320464

PubMed ID

21878396

First Page

15

Last Page

29

Issue

1

Volume

45

Grant

R01LM008912

Fund Ref

U.S. National Library of Medicine

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