Extracting Drug-Drug interaction from text using negation features

Behrouz Bokharaeian , Alberto Díaz , Miguel Ballesteros


Extracting biomedical relations from text is an important task in BioMedical NLP. There are several systems developed for this purpose but the ones on Drug-Drug interactions are still a few. In this paper we want to show the effectiveness of negation features for this task. Therefore, we firstly describe how we extended the DrugDDI corpus by annotating it with the scope of negation, and secondly we report a set of experiments in which we show that negation features provide benefits for the detection of drug-drug interactions in combination with some simple relation extraction methods.

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