Semantic tagging and normalization of French medical entities

Abstract

In this paper we present two tools for facing task 2 in CLEF eHealth 2016. The first one is a semantic tagger aiming to detect relevant entities in French medical documents, tagging them with their appropriate semantic class and normalizing them with the Semantic Groups codes defined in the UMLS. It is based on a distant learning approach that uses several SVM classifiers that are combined to give a single result. The second tool is based on a symbolic procedure to obtain the English translation of each medical term and looks for normalization information in public accessible resources.