Literature DB >> 21646001

Resolution of redundant semantic type assignments for organic chemicals in the UMLS.

C Paul Morrey1, Ling Chen, Michael Halper, Yehoshua Perl.   

Abstract

OBJECTIVE: The Unified Medical Language System (UMLS) integrates terms from different sources into concepts and supplements these with the assignment of one or more high-level semantic types (STs) from its Semantic Network (SN). For a composite organic chemical concept, multiple assignments of organic chemical STs often serve to enumerate the types of the composite's underlying chemical constituents. This practice sometimes leads to the introduction of a forbidden redundant ST assignment, where both an ST and one of its descendants are assigned to the same concept. A methodology for resolving redundant ST assignments for organic chemicals, better capturing the essence of such composite chemicals than the typical omission of the more general ST, is presented.
MATERIALS AND METHODS: The typical SN resolution of a redundant ST assignment is to retain only the more specific ST assignment and omit the more general one. However, with organic chemicals, that is not always the correct strategy. A methodology for properly dealing with the redundancy based on the relative sizes of the chemical components is presented. It is more accurate to use the ST of the larger chemical component for capturing the category of the concept, even if that means using the more general ST.
RESULTS: A sample of 254 chemical concepts having redundant ST assignments in older UMLS releases was audited to analyze the accuracy of current ST assignments. For 81 (32%) of them, our chemical analysis-based approach yielded a different recommendation from the UMLS (2009AA). New UMLS usage notes capturing rules of this methodology are proffered.
CONCLUSIONS: Redundant ST assignments have typically arisen for organic composite chemical concepts. A methodology for dealing with this kind of erroneous configuration, capturing the proper category for a composite chemical, is presented and demonstrated.
Copyright © 2011 Elsevier B.V. All rights reserved.

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Mesh:

Year:  2011        PMID: 21646001      PMCID: PMC3134941          DOI: 10.1016/j.artmed.2011.05.003

Source DB:  PubMed          Journal:  Artif Intell Med        ISSN: 0933-3657            Impact factor:   5.326


  14 in total

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2.  Auditing the UMLS for redundant classifications.

Authors:  Yi Peng; Michael H Halper; Yehoshua Perl; James Geller
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3.  Relating UMLS semantic types and task-based ontology to computer-interpretable clinical practice guidelines.

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

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

5.  Effects of information and machine learning algorithms on word sense disambiguation with small datasets.

Authors:  Gondy Leroy; Thomas C Rindflesch
Journal:  Int J Med Inform       Date:  2005-08       Impact factor: 4.046

6.  Biomedical knowledge navigation by literature clustering.

Authors:  Yasunori Yamamoto; Toshihisa Takagi
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7.  Modeling multi-typed structurally viewed chemicals with the UMLS Refined Semantic Network.

Authors:  Ling Chen; C Paul Morrey; Huanying Gu; Michael Halper; Yehoshua Perl
Journal:  J Am Med Inform Assoc       Date:  2008-10-24       Impact factor: 4.497

8.  Beyond synonymy: exploiting the UMLS semantics in mapping vocabularies.

Authors:  O Bodenreider; S J Nelson; W T Hole; H F Chang
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9.  The UMLS Metathesaurus: representing different views of biomedical concepts.

Authors:  P L Schuyler; W T Hole; M S Tuttle; D D Sherertz
Journal:  Bull Med Libr Assoc       Date:  1993-04

10.  Automated acquisition of disease drug knowledge from biomedical and clinical documents: an initial study.

Authors:  Elizabeth S Chen; George Hripcsak; Hua Xu; Marianthi Markatou; Carol Friedman
Journal:  J Am Med Inform Assoc       Date:  2007-10-18       Impact factor: 4.497

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  2 in total

1.  Auditing the Assignments of Top-Level Semantic Types in the UMLS Semantic Network to UMLS Concepts.

Authors:  Zhe He; Yehoshua Perl; Gai Elhanan; Yan Chen; James Geller; Jiang Bian
Journal:  Proceedings (IEEE Int Conf Bioinformatics Biomed)       Date:  2017-12-18

Review 2.  A review of auditing techniques for the Unified Medical Language System.

Authors:  Ling Zheng; Zhe He; Duo Wei; Vipina Keloth; Jung-Wei Fan; Luke Lindemann; Xinxin Zhu; James J Cimino; Yehoshua Perl
Journal:  J Am Med Inform Assoc       Date:  2020-10-01       Impact factor: 4.497

  2 in total

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