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Book chapter
Open access
English

Automatic annotation of French medical narratives with SNOMED CT concepts

Published inBuilding continents of knowledge in Oceans of data: the future of co-created eHealth, Editors A. Ugon et al. (Eds.), p. 710-714
PublisherAmsterdam : IOS Press
Collection
  • Studies in health technology and informatics; 247
Publication date2018
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
  • Interoperability
  • Narrative data
  • SNOMED CT
  • NLP
Citation (ISO format)
GAUDET-BLAVIGNAC, Christophe et al. Automatic annotation of French medical narratives with SNOMED CT concepts. In: Building continents of knowledge in Oceans of data: the future of co-created eHealth. Amsterdam : IOS Press, 2018. p. 710–714. (Studies in health technology and informatics) doi: 10.3233/978-1-61499-852-5-710
Main files (1)
Book chapter (Published version)
Identifiers
ISBN978-1-61499-852-5
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Technical informations

Creation07/09/2018 4:24:00 PM
First validation07/09/2018 4:24:00 PM
Update time03/15/2023 8:26:27 AM
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