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Using Snomed to recognize and index chemical and drug mentions.

2019-11-01WS 2019Unverified0· sign in to hype

Pilar L{\'o}pez {\'U}beda, Manuel Carlos D{\'\i}az Galiano, L. Alfonso Urena Lopez, Maite Martin

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Abstract

In this paper we describe a new named entity extraction system. Our work proposes a system for the identification and annotation of drug names in Spanish biomedical texts based on machine learning and deep learning models. Subsequently, a standardized code using Snomed is assigned to these drugs, for this purpose, Natural Language Processing tools and techniques have been used, and a dictionary of different sources of information has been built. The results are promising, we obtain 78\% in F1 score on the first sub-track and in the second task we map with Snomed correctly 72\% of the found entities.

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