Intelligent diagnosis with Chinese electronic medical records based on convolutional neural networks.

Journal: BMC bioinformatics
Published Date:

Abstract

BACKGROUND: Benefiting from big data, powerful computation and new algorithmic techniques, we have been witnessing the renaissance of deep learning, particularly the combination of natural language processing (NLP) and deep neural networks. The advent of electronic medical records (EMRs) has not only changed the format of medical records but also helped users to obtain information faster. However, there are many challenges regarding researching directly using Chinese EMRs, such as low quality, huge quantity, imbalance, semi-structure and non-structure, particularly the high density of the Chinese language compared with English. Therefore, effective word segmentation, word representation and model architecture are the core technologies in the literature on Chinese EMRs.

Authors

  • Xiaozheng Li
    College of Computer Science and Technology, Huaqiao University, Xiamen, 361021, China.
  • Huazhen Wang
    College of Computer Science and Technology, Huaqiao University, Xiamen, 361021, China. wanghuazhen@hqu.edu.cn.
  • Huixin He
    College of Computer Science and Technology, Huaqiao University, Xiamen, 361021, China.
  • Jixiang Du
    Department of Computer Science and Engineering, Huaqiao University, Xiamen, China.
  • Jian Chen
    School of Pharmacy, Shanghai Jiaotong University, Shanghai, China.
  • Jinzhun Wu
    Pediatric Department, The First Affiliated Hospital of Xiamen University, Xiamen, 361003, China.