Literature DB >> 1807591

Adding your terms and relationships to the UMLS Metathesaurus.

M S Tuttle1, D D Sherertz, M S Erlbaum, W D Sperzel, L F Fuller, N E Olson, S J Nelson, J J Cimino, C G Chute.   

Abstract

The National Library of Medicine's Unified Medical Language System [1] Metathesaurus contains the richest single corpus of biomedical names in existence. Yet, developers wishing to make use of the Metathesaurus will be confronted by users who want to add local terminology and relationships not already represented there. We urge developers to fill those needs, while, at the same time, they plan for the many consequences of unilateral Metathesaurus enhancement. Foremost among these consequences is the need to maintain local enhancements across subsequent releases of the Metathesaurus. These problems are illustrated via examples of candidate Metathesaurus enhancement terms in use at the Columbia-Presbyterian Medical Center (CPMC), at the Mayo Clinic, and in Current Disease Descriptions (CDD). Sharing and reuse of Metathesaurus enhancement methods may permit local enhancements to be used at other sites, and it may permit the global Metathesaurus utilization effort to benefit from economies of scale.

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Mesh:

Year:  1991        PMID: 1807591      PMCID: PMC2247527     

Source DB:  PubMed          Journal:  Proc Annu Symp Comput Appl Med Care        ISSN: 0195-4210


  14 in total

1.  Representing the UMLS as an object-oriented database: modeling issues and advantages.

Authors:  H Gu; Y Perl; J Geller; M Halper; L M Liu; J J Cimino
Journal:  J Am Med Inform Assoc       Date:  2000 Jan-Feb       Impact factor: 4.497

2.  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

3.  A randomized controlled trial of concept based indexing of Web page content.

Authors:  P L Elkin; A Ruggieri; L Bergstrom; B A Bauer; M Lee; P V Ogren; C G Chute
Journal:  Proc AMIA Symp       Date:  2000

4.  Linking biomedical language information and knowledge resources: GO and UMLS.

Authors:  I N Sarkar; M N Cantor; R Gelman; F Hartel; Y A Lussier
Journal:  Pac Symp Biocomput       Date:  2003

5.  Terminological mapping for high throughput comparative biology of phenotypes.

Authors:  Y A Lussier; J Li
Journal:  Pac Symp Biocomput       Date:  2004

Review 6.  Computational approaches to phenotyping: high-throughput phenomics.

Authors:  Yves A Lussier; Yang Liu
Journal:  Proc Am Thorac Soc       Date:  2007-01

Review 7.  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

8.  A randomized controlled trial of automated term composition.

Authors:  P L Elkin; K R Bailey; C G Chute
Journal:  Proc AMIA Symp       Date:  1998

9.  How useful is the UMLS metathesaurus in developing a controlled vocabulary for an automated problem list?

Authors:  T H Payne; D R Martin
Journal:  Proc Annu Symp Comput Appl Med Care       Date:  1993

10.  Formal properties of the Metathesaurus.

Authors:  M S Tuttle; N E Olson; K E Campbell; D D Sherertz; S J Nelson; W G Cole
Journal:  Proc Annu Symp Comput Appl Med Care       Date:  1994
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