Label-indicator morpheme growth on LSTM for Chinese healthcare question department classification.

Journal: Journal of biomedical informatics
Published Date: Jun 1, 2018

Abstract

BACKGROUND: Current Chinese medicine has an urgent demand for convenient medical services. When facing a large number of patients, understanding patients' questions automatically and precisely is useful. Different from the high professional medical text, patients' questions contain only a small amount of descriptions regarding the symptoms, and the questions are slightly professional and colloquial.

Authors

  • Yang Hu
    Kweichow Moutai Co., Ltd, Renhuai, Guizhou 564501, China.
  • Guihua Wen
    School of Computer Science and Engineering, South China University of Technology, Guangzhou 510000, China. Electronic address: crghwen@scut.edu.cn.
  • Jiajiong Ma
    School of Computer Science and Engineering, South China University of Technology, Guangzhou 510000, China. Electronic address: mullma@outlook.com.
  • Danyang Li
    School of Computer Science and Engineering, South China University of Technology, Guangzhou 510000, China. Electronic address: danyangedu@163.com.
  • Changjun Wang
    Guangdong General Hospital, Guangzhou 510000, China. Electronic address: gzwchj@126.com.
  • Huihui Li
    School of Computer Science and Engineering, South China University of Technology, Guangzhou 510000, China. Electronic address: 29777562@qq.com.
  • Eryang Huan
    School of Computer Science and Engineering, South China University of Technology, Guangzhou 510000, China. Electronic address: huaneryang@gmail.com.

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