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Title

Automatic annotation of French medical narratives with SNOMED CT concepts

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Published in A. Ugon et al. (Eds.). Building continents of knowledge in Oceans of data: the future of co-created eHealth. Amsterdam: IOS Press. 2018, p. 710-714
Abstract Medical data is multimodal. In particular, it is composed of both structured data and narrative data (free text). Narrative data is a type of unstructured data that, although containing valuable semantic and conceptual information, is rarely reused. In order to assure interoperability of medical data, automatic annotation of free text with SNOMED CT concepts via Natural Language Processing (NLP) tools is proposed. This task is performed using a hybrid multilingual syntactic parser. A preliminary evaluation of the annotation shows encouraging results and confirms that semantic enrichment of patient-related narratives can be accomplished by hybrid NLP systems, heavily based on syntax and lexicosemantic resources.
Keywords InteroperabilityNarrative dataSNOMED CTNLP
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ISBN: 978-1-61499-852-5
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Structures
Research groups Laboratoire d'Analyse et de Traitement du Langage (LATL)
Interfaces Homme-machine en milieu clinique (610)
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GAUDET-BLAVIGNAC, Christophe et al. Automatic annotation of French medical narratives with SNOMED CT concepts. In: A. Ugon et al. (Eds.) (Ed.). Building continents of knowledge in Oceans of data: the future of co-created eHealth. Amsterdam : IOS Press, 2018. p. 710-714. https://archive-ouverte.unige.ch/unige:106599

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Deposited on : 2018-07-23

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