Literature DB >> 8591144

Merging terminologies.

M S Tuttle1, O N Suarez-Munist, N E Olson, D D Sherertz, W D Sperzel, M S Erlbaum, L F Fuller, W T Hole, S J Nelson, W G Cole.   

Abstract

A terminology is a systematic, authoritative collection of concept names, or terms, in some domain. No single terminology names all the important concepts in biomedicine. One approach to creating a more comprehensive biomedical terminology is to merge existing biomedical terminologies, as the UMLS( Metathesaurus( has done for the last six years. Because existing terminologies may overlap--for example, one terminology may name a concept also named by another terminologyQthe terminologies in the Metathesaurus must be merged. Some terminologies suggest merges through their structure or content e.g., they suggest synonyms or connections to other terminologies; other merges can be suggested by algorithm. Regardless, all merges in the Metathesaurus must be approved by a human editor with appropriate domain knowledge. By the time Meta-U96 is released early in 1996, one prototype and seven released versions of the Metathesaurus will have been produced by a sequence of four qualitatively different methods, named for the way in which they merge terms: #1 "Term Rewrite Rules, #2 "Transitive Closure on Facts," #3 "Fact-at-a-Time Concept Merging," and #4 "Action-at-a-Time Object Processing." The development of each method has been constrained by the annual Metathesaurus release schedule. The first two methods made the best use of limited computational resources, and the last two make better use of human editing resources.

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Year:  1995        PMID: 8591144

Source DB:  PubMed          Journal:  Medinfo        ISSN: 1569-6332


  9 in total

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

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

2.  Mapping between SNOMED RT and Clinical terms version 3: a key component of the SNOMED CT development process.

Authors:  A Y Wang; J W Barrett; T Bentley; D Markwell; C Price; K A Spackman; M Q Stearns
Journal:  Proc AMIA Symp       Date:  2001

3.  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

4.  A semantic normal form for clinical drugs in the UMLS: early experiences with the VANDF.

Authors:  Stuart J Nelson; Steven H Brown; Mark S Erlbaum; Nels Olson; Tammy Powell; Brian Carlsen; John Carter; Mark S Tuttle; William T Hole
Journal:  Proc AMIA Symp       Date:  2002

5.  An evaluation of hybrid methods for matching biomedical terminologies: mapping the gene ontology to the UMLS.

Authors:  M N Cantor; I N Sarkar; R Gelman; F Hartel; O Bodenreider; Y A Lussier
Journal:  Stud Health Technol Inform       Date:  2003

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

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

Review 7.  Computational approaches to phenotyping: high-throughput phenomics.

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

8.  A UMLS-based method for integrating information databases into an Intranet.

Authors:  F Volot; M Joubert; M Fieschi; D Fieschi
Journal:  Proc AMIA Annu Fall Symp       Date:  1997

9.  Mapping the gene ontology into the unified medical language system.

Authors:  Jane Lomax; Alexa T McCray
Journal:  Comp Funct Genomics       Date:  2004
  9 in total

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