Interpretable time-series neural turing machine for prognostic prediction of patients with type 2 diabetes in physician-pharmacist collaborative clinics.

Journal: International journal of medical informatics
Published Date:

Abstract

BACKGROUND: Type 2 diabetes (T2D) has become a serious health threat globally. However, the existing approaches for diabetes prediction mainly had difficulty in addressing multiple time-series features. This study aims to provide an adjunctive tool for the clinical identification of patients in physician-pharmacist collaborative clinics at high risk of poor prognosis.

Authors

  • Jie Xiao
    Department of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, China; Institute of Clinical Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, China.
  • Bin Chen
    Department of Otorhinolaryngology, Shanghai Sixth People's Hospital, Shanghai Jiao Tong University, Shanghai 200233, China.
  • Lei Chen
    Department of Chemistry, Stony Brook University Stony Brook NY USA.
  • Qing Wang
    School of Chemistry and Chemical Engineering, Southwest Petroleum University, Chengdu 610500, China. qwang@163.com.
  • Shenglan Tan
    Department of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, China; Institute of Clinical Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, China.
  • Haiyan Yuan
    Department of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, China; Institute of Clinical Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, China.
  • Daxiong Xiang
    Department of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, China; Institute of Clinical Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, China.
  • Bikui Zhang
    Department of Clinical Pharmacy, The Second Xiangya Hospital of Central South University, Changsha, China.
  • Xia Li
    Research Center for Macromolecules and Biomaterials, National Institute for Materials Science (NIMS), Tsukuba, Ibaraki, Japan.
  • Shuting Huang
    School of Information Engineering, Guangdong University of Technology, Guangzhou, China.
  • Yuhan Tan
    Institute of Life-Course and Medical Sciences, Faculty of Health and Life Sciences, William Henry Duncan Building, University of Liverpool, Liverpool, UK.
  • Yining Cheng
    Department of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, China; Institute of Clinical Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, China.
  • Wenzheng Xie
    Department of Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, China; Institute of Clinical Pharmacy, The Second Xiangya Hospital, Central South University, Changsha, China.
  • Ping Xu
    Department of Pharmacy, the Second Xiangya Hospital, Central South University, NO139, Renmin Road, Changsha, Hunan 410011, China.