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Construction de plongements de concepts médicaux sans textes

Abstract : In the medical field, many TAL tools are now based on embeddings of concepts from the UMLS.Existing approaches to generate these embeddings require large amounts of medical data. Contraryto these approaches, we propose in this article to rely on Japanese translations of the concepts,more precisely in Kanjis, available in the UMLS to generate these embeddings. Tested on differentevaluation tasks proposed in the literature, our approach, which therefore requires no text, yields goodresults compared to the state of the art. Moreover, we show that it is interesting to combine them withexisting — contextual-based — embeddings.
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https://hal.archives-ouvertes.fr/hal-02784766
Contributor : Sylvain Pogodalla <>
Submitted on : Tuesday, June 23, 2020 - 11:54:35 AM
Last modification on : Thursday, January 7, 2021 - 4:22:03 PM

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  • HAL Id : hal-02784766, version 3

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Vincent Claveau. Construction de plongements de concepts médicaux sans textes. JEP/TALN/RECITAL 2020 - 6e conférence conjointe Journées d'Études sur la Parole (JEP, 33e édition), Traitement Automatique des Langues Naturelles (TALN, 27e édition), Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RÉCITAL, 22e édition). Volume 2 : Traitement Automatique des Langues Naturelles, Jun 2020, Nancy, France. pp.181-188. ⟨hal-02784766v3⟩

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