Semantic reclassification of the UMLS concepts

Jung Wei Fan; Carol Friedman

doi:10.1093/bioinformatics/btn343

Semantic reclassification of the UMLS concepts

Jung Wei Fan, Carol Friedman

Digital Health Sciences

Research output: Contribution to journal › Article › peer-review

12 Scopus citations

Abstract

Accurate semantic classification is valuable for text mining and knowledge-based tasks that perform inference based on semantic classes. To benefit applications using the semantic classification of the Unified Medical Language System (UMLS) concepts, we automatically reclassified the concepts based on their lexical and contextual features. The new classification is useful for auditing the original UMLS semantic classification and for building biomedical text mining applications.

Original language	English (US)
Pages (from-to)	1971-1973
Number of pages	3
Journal	Bioinformatics
Volume	24
Issue number	17
DOIs	https://doi.org/10.1093/bioinformatics/btn343
State	Published - Sep 2008

ASJC Scopus subject areas

Statistics and Probability
Biochemistry
Molecular Biology
Computer Science Applications
Computational Theory and Mathematics
Computational Mathematics

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10.1093/bioinformatics/btn343

Cite this

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title = "Semantic reclassification of the UMLS concepts",

abstract = "Accurate semantic classification is valuable for text mining and knowledge-based tasks that perform inference based on semantic classes. To benefit applications using the semantic classification of the Unified Medical Language System (UMLS) concepts, we automatically reclassified the concepts based on their lexical and contextual features. The new classification is useful for auditing the original UMLS semantic classification and for building biomedical text mining applications.",

author = "Fan, {Jung Wei} and Carol Friedman",

note = "Funding Information: Funding: This work was supported by Grants R01 LM7659 and R01 LM8635 from the National Library of Medicine of USA.",

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AB - Accurate semantic classification is valuable for text mining and knowledge-based tasks that perform inference based on semantic classes. To benefit applications using the semantic classification of the Unified Medical Language System (UMLS) concepts, we automatically reclassified the concepts based on their lexical and contextual features. The new classification is useful for auditing the original UMLS semantic classification and for building biomedical text mining applications.

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Semantic reclassification of the UMLS concepts

Abstract

ASJC Scopus subject areas

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