Comparison and development of machine learning tools in the prediction of chronic kidney disease progression.

Journal: Journal of translational medicine
Published Date: Apr 11, 2019

Abstract

BACKGROUND: Urinary protein quantification is critical for assessing the severity of chronic kidney disease (CKD). However, the current procedure for determining the severity of CKD is completed through evaluating 24-h urinary protein, which is inconvenient during follow-up.

Authors

  • Jing Xiao
    Xiyuan Hospital, China Academy of Chinese Medical Sciences(CACMS), Beijing, China.
  • Ruifeng Ding
    School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China.
  • Xiulin Xu
    School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China.
  • Haochen Guan
    Department of Nephrology, Huadong Hospital Affiliated To Fudan University, Shanghai, 200040, China.
  • Xinhui Feng
    Department of Nephrology, Huadong Hospital Affiliated To Fudan University, Shanghai, 200040, China.
  • Tao Sun
    Janssen Research & Development, LLC, Raritan, NJ, USA.
  • Sibo Zhu
    MOE Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai, 200438, China. sibozhu@fudan.edu.cn.
  • Zhibin Ye
    Department of Nephrology, Huadong Hospital Affiliated To Fudan University, Shanghai, 200040, China. yezhibin3@126.com.

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