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Translating ICD-11 into French using lexical-based approach: a preliminary study
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In: ISSN: 0926-9630 ; EISSN: 1879-8365 ; Studies in Health Technology and Informatics ; https://hal.archives-ouvertes.fr/hal-02103587 ; Studies in Health Technology and Informatics, IOS Press, 2015, 216, pp.1036 (2015)
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Assisting the Translation of SNOMED CT into French.
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In: ISSN: 0926-9630 ; EISSN: 1879-8365 ; Studies in Health Technology and Informatics ; https://www.hal.inserm.fr/inserm-00854301 ; Studies in Health Technology and Informatics, IOS Press, 2013, 192, pp.47-51 (2013)
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Assisting the Translation of SNOMED CT into French.
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In: ISSN: 0926-9630 ; EISSN: 1879-8365 ; Studies in Health Technology and Informatics ; https://hal.inria.fr/hal-00854309 ; Studies in Health Technology and Informatics, IOS Press, 2013, 192, pp.47-51 (2013)
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Integrating the Human Phenotype Ontology into HeTOP Terminology-Ontology Server.
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In: ISSN: 0926-9630 ; EISSN: 1879-8365 ; Studies in Health Technology and Informatics ; https://www.hal.inserm.fr/inserm-00854299 ; Studies in Health Technology and Informatics, IOS Press, 2013, 192, pp.961 (2013)
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Translating the Foundational Model of Anatomy into French using knowledge-based and lexical methods
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In: ISSN: 1472-6947 ; EISSN: 1472-6947 ; BMC Medical Informatics and Decision Making ; https://hal.archives-ouvertes.fr/hal-00645338 ; BMC Medical Informatics and Decision Making, BioMed Central, 2011, 11 (1), pp.65. ⟨10.1186/1472-6947-11-65⟩ (2011)
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Abstract:
International audience ; BACKGROUND: The Foundational Model of Anatomy (FMA) is the reference ontology regarding human anatomy. FMA vocabulary was integrated into the Health Multi Terminological Portal (HMTP) developed by CISMeF based on the CISMeF Information System which also includes 26 other terminologies and controlled vocabularies, mainly in French. However, FMA is primarily in English. In this context, the translation of FMA English terms into French could also be useful for searching and indexing French anatomy resources. Various studies have investigated automatic methods to assist the translation of medical terminologies or create multilingual medical vocabularies. The goal of this study was to facilitate the translation of FMA vocabulary into French. METHODS: We compare two types of approaches to translate the FMA terms into French. The rst one is UMLS-based on the conceptual information of the UMLS metathesaurus. The second method is lexically-based on several Natural Language Processing (NLP) tools. RESULTS: The UMLS-based approach produced a translation of 3,661 FMA terms into French whereas the lexical approach produced a translation of 3,129 FMA terms into French. A qualitative evaluation was made on 100 FMA terms translated by each method. For the UMLS-based approach, among the 100 translations, 52% were manually rated as "very good" and only 7% translations as "bad". For the lexical approach, among the 100 translations, 47% were rated as "very good" and 20% translations as "bad". CONCLUSIONS: Overall, a low rate of translations were demonstrated by the two methods. The two approaches permitted us to semi-automatically translate 3,776 FMA terms from English into French, this was to added to the existing 10,844 French FMA terms in the HMTP (4,436 FMA French terms and 6,408 FMA terms manually translated).
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Keyword:
[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]; [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]; [SDV.MHEP.AHA]Life Sciences [q-bio]/Human health and pathology/Tissues and Organs [q-bio.TO]; Narration
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URL: https://hal.archives-ouvertes.fr/hal-00645338
https://doi.org/10.1186/1472-6947-11-65
https://hal.archives-ouvertes.fr/hal-00645338/document
https://hal.archives-ouvertes.fr/hal-00645338/file/1472-6947-11-65.pdf
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Translating the foundational model of anatomy into french using knowledge-based and lexical methods
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Assisting the Translation of SNOMED CT into French using UMLS and four Representative French-language Terminologies
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