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Mapping medical vocabularies to the Unified Medical Language System.

Authors: Q, Zeng; J J, Cimino;

Mapping medical vocabularies to the Unified Medical Language System.

Abstract

This paper presents our work in automated mapping of medical vocabularies to the National Library of Medicine's Unified Medical Language System (UMLS). We used the UMLS Knowledge Source (KS) tool to map terms from several sources to UMLS Metathesaurus concepts. We compared performance of the KS tools with our own Minimal Representable Units Method (MRUM). The KS tools were able to map terms from 13% to 54% of the time, depending on the term set and the KS options used. Our MRUM method mapped between 96% and 99% of the terms. Based on our experience, we believe that questions remain about the best method by which the UMLS can be used to achieve automated term translation.

Related Organizations
Keywords

Systems Integration, Electronic Data Processing, Vocabulary, Controlled, Unified Medical Language System, Algorithms

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    influence
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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
15
Average
Top 10%
Top 10%
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