A hybrid neural network model for predicting kidney disease in hypertension patients based on electronic health records.

Journal: BMC medical informatics and decision making
Published Date:

Abstract

BACKGROUND: Disease prediction based on Electronic Health Records (EHR) has become one hot research topic in biomedical community. Existing work mainly focuses on the prediction of one target disease, and little work is proposed for multiple associated diseases prediction. Meanwhile, a piece of EHR usually contains two main information: the textual description and physical indicators. However, existing work largely adopts statistical models with discrete features from numerical physical indicators in EHR, and fails to make full use of textual description information.

Authors

  • Yafeng Ren
    Guangdong Collaborative Innovation Center for Language Research & Services, Guangdong University of Foreign Studies, Guangzhou, 510420, Guangdong, China.
  • Hao Fei
    School of Cyber Science and Engineering, Wuhan University, Wuhan, China.
  • Xiaohui Liang
    Department of Computer Science, University of Massachusetts, Boston, MA, United States.
  • Donghong Ji
    School of Computer, Wuhan University, Wuhan, 430072, China. dhji@whu.edu.cn.
  • Ming Cheng