Extracting Drug-Drug interaction from text using negation features

• Autores: Behrouz Bokharaeian, Alberto Díaz Esteban , Miguel Ballesteros
• Localización: Procesamiento del lenguaje natural, ISSN 1135-5948, Nº. 51, 2013, págs. 49-56
• Idioma: inglés
• Enlaces
  • Texto completo
• Resumen
  • español

    La extraccion de relaciones entre entidades es una tarea muy importante dentro del procesamiento de textos biomedicos. Se han desarrollado muchos algoritmos para este proposito aunque solo unos pocos han estudiado el tema de las interacciones entre farmacos. En este trabajo se ha estudiado el efecto de la negacion para esta tarea. En primer lugar, se describe como se ha extendido el corpus DrugDDI con anotaciones sobre negaciones y, en segundo lugar, se muestran una serie de experimentos en los que se muestra que tener en cuenta el efecto de la negacion puede mejorar la deteccion de interacciones entre farmacos cuando se combina con otros metodos de extraccion de relaciones.

  • English

    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. We rstly 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 bene ts for the detection of drug-drug interactions in combination with some simple relation extraction methods.

• Referencias bibliográficas
  • Amini, I., M. Sanderson, D. Martinez y X. Li. 2011. Search for clinical records: Rmit at trec 2011 medical track. En Proceedings of the 20th...
  • Aronson, A. 2001. Effective mapping of biomedical text to the UMLS Metathesaurus: the MetaMap program. En Proceedings of the AMIA Symposium,...
  • Ballesteros, M., V. Francisco, A. Diaz, J. Herrera y P. Gervas. 2012. Inferring the scope of negation in biomedical documents. En Proceedings...
  • Bunescu, R., R. Ge, R. Kate, E. Marcotte, R. Mooney, A. Ramani y Y. Wong. 2005. Comparative experiments on learning information extractors...
  • Bunescu R. y R. Mooney. 2005. A shortest path dependency kernel for relation extraction. En Proceedings of the conference on Human Language...
  • Cer, D., M. de Marneffe, D. Jurafsky y C. D. Manning. 2010. Parsing to Stanford Dependencies: Trade-offs between speed and accuracy. En Proceedings...
  • Chapman, W., W. Bridewell, P. Hanbury, G. F. Cooper y B. G. Buchanan. 2001. A Simple Algorithm for Identifying Negated Findings and Diseases...
  • Chen, Y., F. Liu y B. Manderick. 2011. Extract Protein-Protein Interactions From the Literature Using Support Vector Machines with Feature...
  • Frunza, O. y D. Inkpen. 2010. Extraction of disease-treatment semantic relations from biomedical sentences. Proceedings of the 2010 Workshop...
  • Giuliano, C., A. Lavelli y L. Romano. 2005. Exploiting shallow linguistic information for relation extraction from biomedical literature....
  • Guodong, Z., Q. Longhua y F. Jianxi. 2010. Tree kernel-based semantic relation extraction with rich syntactic and semantic information. International...
  • Krallinger, M., A. Valencia y L. Hirschman. 2008. Linking genes to literature: text mining, information extraction, and retrieval applications...
  • Moschitti, A. 2006. Making Tree Kernels Practical for Natural Language Learning. En Proccedings of the 11th Conference of the European Chapter...
  • Nedellec, C. 2004. Machine Learning for Information Extraction in Genomics - State of the Art and Perspectives. Text Mining and its Applications,...
  • Neuhaus, M. y H. Bunke. 2006. A Random Walk Kernel Derived from Graph Edit Distance. Lecture Notes in Computer Sci- ence, 4109(5):191-199.
  • Platt, J. 1998. Sequential Minimal Optimization: A Fast Algorithm for Training Support Vector Machines. Advances in kernel methods - Support...
  • Pyysalo, S., A. Airola, J. Heimonen, J. Bjorne, F. Ginter y T. Salakoski. 2008. Comparative analysis of five proteinprotein interaction corpora....
  • Segura-Bedmar, I., P. Martínez y D. Sánchez-Cisneros. 2011. En Proceedings of the 1st Challenge task on Drug-Drug Interaction Extraction (DDIExtraction...
  • Segura-Bedmar, I., P. Martínez y C. de Pablo Sánchez. 2011. Using a shallow linguistic kernel for drug-drug interaction extraction. Journal...
  • Simões, G., D. Matos y H. Galhardas. 2013. A Labeled Graph Kernel for Relationship Extraction. CoRR, abs/1302.4874.
  • Stockley, I. H. 2007. Stockley's Drug Interaction. Pharmaceutical Press.
  • Thomas, P., M. Neves, I. Solt, D. Tikk y U. Leser. 2011. Relation extraction for drugdrug interactions using ensemble learning. En Proceedings...
  • Vincze, V., G. Szarvas, R. Farkas, G. Mora y J. Csirik. 2008. The BioScope corpus: annotation for negation, uncertainty and their scope in...
  • Wishart, D. R., C. Knox , A. C. Guo, D. Cheng, S. Shrivastava, D. Tzur, B. Gautam, M. Hassanali. 2008. DrugBank: a knowledgebase for drugs,...