LIST-LUX: Disorder Identification from Clinical Texts
Asma Ben Abacha, Aikaterini Karanasiou, Yassine Mrabet, Júlio Cesar dos Reis · 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, second, on a similarity measure and SNOMED to determine the relevant CUI.We present and discuss the obtained results on the development corpus and the official test corpus.