Biomedical event extraction with a novel combination strategy based on hybrid deep neural networks.

Journal: BMC bioinformatics
Published Date:

Abstract

BACKGROUND: Biomedical event extraction is a fundamental and in-demand technology that has attracted substantial interest from many researchers. Previous works have heavily relied on manual designed features and external NLP packages in which the feature engineering is large and complex. Additionally, most of the existing works use the pipeline process that breaks down a task into simple sub-tasks but ignores the interaction between them. To overcome these limitations, we propose a novel event combination strategy based on hybrid deep neural networks to settle the task in a joint end-to-end manner.

Authors

  • Lvxing Zhu
    School of Computer Science and Technology, University of Science and Technology of China, Huangshan Road, Hefei, 230026, People's Republic of China.
  • Haoran Zheng
    School of Computer Science and Technology, University of Science and Technology of China, Huangshan Road, Hefei, 230026, People's Republic of China. zhulx@mail.ustc.edu.cn.