Deep learning model to predict lupus nephritis renal flare based on dynamic multivariable time-series data.

Journal: BMJ open
Published Date:

Abstract

OBJECTIVES: To develop an interpretable deep learning model of lupus nephritis (LN) relapse prediction based on dynamic multivariable time-series data.

Authors

  • Siwan Huang
    Ping An Healthcare Technology, Beijing, China.
  • Yinghua Chen
    National Clinical Research Centre of Kidney Diseases, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China.
  • Yanan Song
    Department of Endocrinology of the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
  • Kaiyuan Wu
    Ping An Healthcare Technology, Beijing, China.
  • Tiange Chen
    Ping An Healthcare Technology, Beijing.
  • Yuan Zhang
    Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Wenxiao Jia
    Ping An Healthcare Technology, Beijing, China.
  • Hai-Tao Zhang
    School of Artificial Intelligence and Automation, MOE Key Lab of Intelligent Control and Image Processing, Huazhong University of Science and Technology, Wuhan 430074, China.
  • Dan-Dan Liang
  • Jing Yang
    Beijing Novartis Pharma Co. Ltd., Beijing, China.
  • Cai-Hong Zeng
    National Clinical Research Centre of Kidney Diseases, Jinling Hospital, Nanjing University School of Medicine, Nanjing, Jiangsu, China.
  • Xiang Li
    Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
  • Zhi-Hong Liu
    National Clinical Research Centre of Kidney Diseases, Jinling Hospital, Nanjing University School of Medicine, Nanjing, Jiangsu, China lixiang453@pingan.com.cn liuzhihong@nju.edu.cn.