a single kernel-based approach to extract drug-drug interactions from biomedical literature一个基于内核的方法从生物医学文献中提取药物之间的相互作用.pdfVIP

A Single Kernel-Based Approach to Extract Drug-Drug Interactions from Biomedical Literature Yijia Zhang*, Hongfei Lin, Zhihao Yang, Jian Wang, Yanpeng Li College of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning, China Abstract When one drug influences the level or activity of another drug this is known as a drug-drug interaction (DDI). Knowledge of such interactions is crucial for patient safety. However, the volume and content of published biomedical literature on drug interactions is expanding rapidly, making it increasingly difficult for DDIs database curators to detect and collate DDIs information manually. In this paper, we propose a single kernel-based approach to extract DDIs from biomedical literature. This novel kernel-based approach can effectively make full use of syntactic structural information of the dependency graph. In particular, our approach can efficiently represent both single subgraph topological information and the relation of two subgraphs in the dependency graph. Experimental evaluations showed that our single kernel-based approach can achieve state-of-the-art performance on the publicly available DDI corpus without exploiting multiple kernels or additional domain resources. Citation: Zhang Y, Lin H, Yang Z, Wang J, Li Y (2012) A Single Kernel-Based Approach to Extract Drug-Drug Interactions from Biomedical Literature. PLoS ONE 7(11): e48901. doi:10.1371/journal.pone.0048901 Editor: Luis Mateus Rocha, Indiana University, United States of America Received February 28, 2012; Accepted September 6, 2012; Published November 1, 2012 Copyright: 2012 Zhang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original auth