title: Text mining for pharmacovigilance: Using machine learning for drug name recognition and drug-drug interaction extraction and classification.
abstract: Pharmacovigilance (PV) is defined by the World Health Organization as the science and activities related to the detection, assessment, understanding and prevention of adverse effects or any other drug-related problem. An essential aspect in PV is to acquire knowledge about Drug-Drug Interactions (DDIs). The shared tasks on DDI-Extraction organized in 2011 and 2013 have pointed out the importance of this issue and provided benchmarks for: Drug Name Recognition, DDI extraction and DDI classification. In this paper, we present our text mining systems for these tasks and evaluate their results on the DDI-Extraction benchmarks. Our systems rely on machine learning techniques using both feature-based and kernel-based methods. The obtained results for drug name recognition are encouraging. For DDI-Extraction, our hybrid system combining a feature-based method and a kernel-based method was ranked second in the DDI-Extraction-2011 challenge, and our two-step system for DDI detection and classification was ranked first in the DDI-Extraction-2013 task at SemEval. We discuss our methods and results and give pointers to future work.
authors.affiliation: Luxembourg Institute of Science and Technology, Luxembourg. Electronic address: asma.benabacha@list.lu.
authors.forename: Asma
authors.initials: A
authors.lastname: Ben Abacha
authors.affiliation: IBM Research, NY, USA. Electronic address: mchowdh@us.ibm.com.
authors.forename: Md Faisal Mahbub
authors.initials: MFM
authors.lastname: Chowdhury
authors.affiliation: Luxembourg Institute of Science and Technology, Luxembourg. Electronic address: aikaterini.karanasiou@list.lu.
authors.forename: Aikaterini
authors.initials: A
authors.lastname: Karanasiou
authors.affiliation: Luxembourg Institute of Science and Technology, Luxembourg. Electronic address: yassine.mrabet@list.lu.
authors.forename: Yassine
authors.initials: Y
authors.lastname: Mrabet
authors.affiliation: HLT Research Unit, FBK, Trento, Italy. Electronic address: lavelli@fbk.eu.
authors.forename: Alberto
authors.initials: A
authors.lastname: Lavelli
authors.affiliation: LIMSI-CNRS, Orsay, France. Electronic address: pz@limsi.fr.
authors.forename: Pierre
authors.initials: P
authors.lastname: Zweigenbaum
mesh_terms: D057225:Data Mining; D004347:Drug Interactions; D000069550:Machine Learning; D060735:Pharmacovigilance
keywords: Drug name recognition; Drug–drug interactions; Machine learning; Pharmacovigilance; Text mining