Assisting the Translation of SNOMED CT into French using UMLS and four Representative French-language Terminologies

OBJECTIVE To provide a semantics-based method to assist the translation of SNOMED CT into French. To do so, we selected four French-language terminologies: ICD-10, SNOMED International, MedDRA, MeSH, as they are dedicated to different uses - epidemiology, clinical medicine, adverse reactions, medical literature, respectively - in order to map them to SNOMED Clinical Terms (CT), and thus associate French terms with SNOMED CT concepts. In this way, we measured the number of SNOMED CT concepts to be found in French-language terminologies. MATERIAL AND METHOD We used the UMLS Metathesaurus. The mapping method was based on the coincidence of identifiers and on the explicit mappings present in the Metathesaurus. RESULTS The study dealt exclusively with preferred terms (PTs) in the terminologies. The terminologies are mapped with varying success as regards PTs mapped to SNOMED terms (from 52% to 96%). Conversely, 45% of SNOMED CT terms are mapped by uniting the four terminologies. DISCUSSION A more effective mapping technique than the current method is under consideration. CONCLUSION The method presented will be refined. It could certainly provide useful assistance in the translation of SNOMED CT into French. Due to its general nature, it could be used to translate SNOMED CT into other languages than French.

[1]  F B ROGERS,et al.  Medical Subject Headings , 1948, Nature.

[2]  Olivier Bodenreider,et al.  Investigating subsumption in SNOMED CT: An exploration into large description logic-based biomedical terminologies , 2007, Artif. Intell. Medicine.

[3]  Ronald Cornet,et al.  Do SNOMED CT Relationships Qualify? , 2008, MIE.

[4]  E. Brown,et al.  The Medical Dictionary for Regulatory Activities (MedDRA) , 1999, Drug safety.

[5]  F. Jones,et al.  International Classification of Diseases , 1978 .

[6]  Kent A. Spackman,et al.  Role grouping as an extension to the description logic of Ontylog, motivated by concept modeling in SNOMED , 2002, AMIA.

[7]  J J Cimino,et al.  From ICD9-CM to MeSH using the UMLS: a how-to guide. , 1993, Proceedings. Symposium on Computer Applications in Medical Care.

[8]  D. Lindberg,et al.  The Unified Medical Language System , 1993, Methods of Information in Medicine.

[9]  Christopher G. Chute,et al.  Viewpoint Paper: Auditing the Semantic Completeness of SNOMED CT Using Formal Concept Analysis , 2009, J. Am. Medical Informatics Assoc..

[10]  Daniel J. Vreeman,et al.  Logical Observation Identifiers Names and Codes (LOINC®) users' guide , 2010 .

[11]  Paul Fabry,et al.  Vers une version franeaise de la SNOMED CT , 2009 .

[12]  Nicola Guarino,et al.  Some Ontological Principles for Designing Upper Level Lexical Resources , 1998, LREC.

[13]  Y. Lussier,et al.  The SNOMED Model: A Knowledge Source for the Controlled Terminology of the Computerized Patient Record , 1998, Methods of Information in Medicine.

[14]  Franz Baader,et al.  SNOMED reaching its adolescence: Ontologists' and logicians' health check , 2009, Int. J. Medical Informatics.

[15]  B. Bentsen.  International classification of primary care. , 1986, Scandinavian journal of primary health care.

[16]  Olivier Bodenreider,et al.  Utilizing the UMLS for Semantic Mapping between Terminologies , 2005, AMIA.

[17]  Olivier Bodenreider,et al.  Beyond synonymy: exploiting the UMLS semantics in mapping vocabularies , 1998, AMIA.

[18]  Kent A. Spackman,et al.  Compositional concept representation using SNOMED: towards further convergence of clinical terminologies , 1998, AMIA.