PROGRAM


16.00-16.30 - Welcome

16.30-17.00 - Relation Extraction for Drug-Drug Interactions using Ensemble Learning. Mariana Neves. Institut für Informatik, Humboldt-Universität zu Berlin

17.00-17.30 - Drug-Drug Interaction Extraction with SVM and RLS Classifiers. Jari Björne. University of Turku

17.30-18.30 - Poster session with coffee:

  • Automatic Drug-Drug Interaction Detection: A Machine Learning Approach With Maximal Frequent Sequence Extraction. Sandra Garcia-Blasco, Santiago M. Mola-Velasco, Roxana Danger and Paolo Rosso.
  • Extraction of drug-drug interactions using all paths graph kernel. Shreyas Karnik, Abhinita Subhadarshini, Zhiping Wang, Luis M. Rocha and Lang Li.
  • Drug-Drug Interactions Discovery Based on CRFs SVMs and Rule-Based Methods. Stefania Rubrichi, Matteo Gabetta, Riccardo Bellazzi, Cristiana Larizza and Silvana Quaglini
  • A Machine Learning Approach to Extract Drug ¿ Drug Interactions in an Unbalanced Dataset. Jacinto Mata Vázquez, Ramón Santano, Daniel Blanco, Marcos Lucero and Manuel J. Maña López
  • An Experimental Exploration of Drug-Drug Interaction extraction from biomedical texts. Man Lan, Jiang Zhao, Kezun Zhang, Jingli Cai and Honglei Shi

18.30-19.00 - Drug-drug Interaction Extraction Using Composite Kernels. Md. Faisal Mahbub Chowdhury. FBK

19.00-19.30 - Two Different Machine Learning Techniques for Drug-Drug Interaction Extraction. Asma Ben Abacha, LIMSI

19.30-20.00 - Feature selection for Drug-Drug Interaction detection using machine-learning based approaches. Anne-Lyse Minard, LIMSI - CNRS.

20.00-20.15 - Final remarks.

Universidad Carlos III de Madrid - Departamento de informática - Grupo de bases de datos

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