Automatic Annotation of French Medical Narratives with SNOMED CT Concepts
Gaudet-Blavignac, C.; Foufi, V.; Wehrli, E.; Lovis, C.
Studies in Health Technology and Informatics 247: 710-714
2018
ISSN/ISBN: 0926-9630 PMID: 29678053 Document Number: 696714
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.