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Mapping the ATC Classification to the UMLS Metathesaurus: Some Pragmatic Applications

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ATC classification is a WHO international classification used to classify drugs. The aim of this paper is to evaluate two lexical methods in English and in French to map ATC to UMLS. Several applications have been impemented to illustrate the use of the ATC mapping in English and French: (a) MeSH translation in Norwegian, (b) Drug Information Portal, and (c) ATC to PubMed tool. Two lexical methods were used to map ATC to UMLS. The first approach used a French natural language processing tool to map French terms of ATC to the French terminologies of UMLS. The second approach used the MetaMap tool to map English terms of ATC to UMLS. The English MetaMap provides slightly more mappings than the French NLP tool (3,170 vs. 2,992). On the other hand, the French NLP tool provides a slightly better precision than MetaMap (88% vs. 86%). Using a manual mapping between ATC and MeSH, the union of the validated mappings between ATC and MeSH provides 2,824 mappings (68.7% of ATC codes of the fifth level). Lexical methods are powerful methods to map health terminologies to the UMLS Metathesaurus. Manual mapping is still necessary to complete the mapping.
Title: Mapping the ATC Classification to the UMLS Metathesaurus: Some Pragmatic Applications
Description:
ATC classification is a WHO international classification used to classify drugs.
The aim of this paper is to evaluate two lexical methods in English and in French to map ATC to UMLS.
Several applications have been impemented to illustrate the use of the ATC mapping in English and French: (a) MeSH translation in Norwegian, (b) Drug Information Portal, and (c) ATC to PubMed tool.
Two lexical methods were used to map ATC to UMLS.
The first approach used a French natural language processing tool to map French terms of ATC to the French terminologies of UMLS.
The second approach used the MetaMap tool to map English terms of ATC to UMLS.
The English MetaMap provides slightly more mappings than the French NLP tool (3,170 vs.
2,992).
On the other hand, the French NLP tool provides a slightly better precision than MetaMap (88% vs.
86%).
Using a manual mapping between ATC and MeSH, the union of the validated mappings between ATC and MeSH provides 2,824 mappings (68.
7% of ATC codes of the fifth level).
Lexical methods are powerful methods to map health terminologies to the UMLS Metathesaurus.
Manual mapping is still necessary to complete the mapping.

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