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LIST-LUX: Disorder Identification from Clinical Texts
2015
Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)
This paper describes our participation in task 14 of SemEval 2015. This task focuses on the analysis of clinical texts and includes: (i) the recognition of the span of a disorder mention and (ii) its normalization to a unique concept identifier in the UMLS/SNOMED-CT terminology. We propose a two-step approach which relies first on Conditional Random Fields to detect textual mentions of disorders using different lexical, syntactic, orthographic and semantic features such as ontologies and,
doi:10.18653/v1/s15-2074
dblp:conf/semeval/AbachaKMR15
fatcat:kfrm7mtb3fdkhjvignpchh4sem