Extraction of drug-drug interactions using all paths graph kernel

Shreyas Karnik, Abhinita Subhadarshini, Zhiping Wang, Luis M. Rocha, Lang Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Drug-drug interactions (DDIs) cause nearly 3% of all hospital admissions. Regulatory authorities such as the Food and Drug Administration (FDA) and the pharmaceutical companies keep a rigorous tab on the DDIs. The major source of DDI information is the biomedical literature. In this paper we present a DDI extraction approach based on all paths graph kernel [1] from the DrugDDI corpus [2]. We also evaluate the method on an in-house developed clinical in vivo pharmacokinetic DDI corpus. When the DDI extraction model was evaluated on the test dataset from both corpora we recorded a F-score of 0.658 on the clinical in vivo pharmacokinetic DDI corpus and 0.16 on the DrugDDI corpus.

Original languageEnglish
Title of host publicationCEUR Workshop Proceedings
Pages83-88
Number of pages6
Volume761
StatePublished - 2011
Event1st Challenge Task on Drug-Drug Interaction Extraction 2011, DDIExtraction 2011 - Co-located with the 27th Conference of the Spanish Society for Natural Language Processing, SEPLN 2011 - Huelva, Spain
Duration: Sep 7 2011Sep 7 2011

Other

Other1st Challenge Task on Drug-Drug Interaction Extraction 2011, DDIExtraction 2011 - Co-located with the 27th Conference of the Spanish Society for Natural Language Processing, SEPLN 2011
CountrySpain
CityHuelva
Period9/7/119/7/11

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ASJC Scopus subject areas

  • Computer Science(all)

Cite this

Karnik, S., Subhadarshini, A., Wang, Z., Rocha, L. M., & Li, L. (2011). Extraction of drug-drug interactions using all paths graph kernel. In CEUR Workshop Proceedings (Vol. 761, pp. 83-88)