Attention-based deep residual learning network for entity relation extraction in Chinese EMRs.

Journal: BMC medical informatics and decision making
Published Date:

Abstract

BACKGROUND: Electronic medical records (EMRs) contain a variety of valuable medical concepts and relations. The ability to recognize relations between medical concepts described in EMRs enables the automatic processing of clinical texts, resulting in an improved quality of health-related data analysis. Driven by the 2010 i2b2/VA Challenge Evaluation, the relation recognition problem in EMRs has been studied by many researchers to address this important aspect of EMR information extraction.

Authors

  • Zhichang Zhang
    College of Computer Science and Engineering,Northwest Normal University, 967 Anning East Road, Lanzhou, 730070, China. zhichangzhang@qq.com.
  • Tong Zhou
    College of Computer Science and Engineering, Northwest Normal University, Lanzhou, 730070, China.
  • Yu Zhang
    College of Marine Electrical Engineering, Dalian Maritime University, Dalian, China.
  • Yali Pang
    College of Computer Science and Engineering,Northwest Normal University, 967 Anning East Road, Lanzhou, 730070, China.