An attention-based effective neural model for drug-drug interactions extraction.

Journal: BMC bioinformatics
Published Date: Oct 10, 2017

Abstract

BACKGROUND: Drug-drug interactions (DDIs) often bring unexpected side effects. The clinical recognition of DDIs is a crucial issue for both patient safety and healthcare cost control. However, although text-mining-based systems explore various methods to classify DDIs, the classification performance with regard to DDIs in long and complex sentences is still unsatisfactory.

Authors

  • Wei Zheng
    School of Computer Engineering, Jinling Institute of Technology, Nanjing, 211169, China. zhengwei@jit.edu.cn.
  • Hongfei Lin
  • Ling Luo
    Department of Epidemiology and Medical Statistics School of Public Health, Guangdong Medical University, Dongguan, Guangdong, China.
  • Zhehuan Zhao
    College of Computer Science and Technology, Dalian University of Technology, Dalian, China.
  • Zhengguang Li
    College of Computer Science and Technology, Dalian University of Technology, Dalian, China.
  • Yijia Zhang
    School of Computer Science and Technology, Dalian University of Technology, Dalian, China.
  • Zhihao Yang
    College of Computer Science and Technology, Dalian University of Technology, Dalian 116024, China.
  • Jian Wang
    Veterinary Diagnostic Center, Shanghai Animal Disease Control Center, Shanghai, China.

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