ArticleJournal of biomedical informatics2009
Auditing associative relations across two knowledge sources.
Article in Journal of biomedical informatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- A review of auditing techniques for the Unified Medical Language System.Journal of the American Medical Informatics Association : JAMIA · 2020Review
- Exploiting UMLS semantics for checking semantic consistency among UMLS concepts.Studies in health technology and informatics · 2010Article
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3 authors.
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Abstract
objectivesThis paper proposes a novel semantic method for auditing associative relations in biomedical terminologies. We tested our methodology on two Unified Medical Language System (UMLS) knowledge sources.
methodsWe use the UMLS semantic groups as high-level representations of the domain and range of relationships in the Metathesaurus and in the Semantic Network. A mapping created between Metathesaurus relationships and Semantic Network relationships forms the basis for comparing the signatures of a given Metathesaurus relationship to the signatures of the semantic relationship to which it is mapped. The consistency of Metathesaurus relations is studied for each relationship.
resultsOf the 177 associative relationships in the Metathesaurus, 84 (48%) exhibit a high-degree of consistency with the corresponding Semantic Network relationships. Overall, 63% of the 1.8 M associative relations in the Metathesaurus are consistent with relations in the Semantic Network.
conclusionThe semantics of associative relationships in biomedical terminologies should be defined explicitly by their developers. The Semantic Network would benefit from being extended with new relationships and with new relations for some existing relationships. The UMLS editing environment could take advantage of the correspondence established between relationships in the Metathesaurus and the Semantic Network. Finally, the auditing method also yielded useful information for refining the mapping of associative relationships between the two sources.
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