Construction of artificial intelligence non-invasive diagnosis model for common glomerular diseases based on hyperspectral and urine analysis.

Journal: Photodiagnosis and photodynamic therapy
PMID: 37597684

Abstract

OBJECTIVE: To develop a non-invasive fluid biopsy assisted diagnosis model for glomerular diseases based on hyperspectral, so as to solve the problem of poor compliance of patients with invasive examination and improve the early diagnosis rate of glomerular diseases.

Authors

  • Xiangyu Hou
    Department of Nephrology, Shandong Institute of Nephrology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, No. 16766 Jingshi Road, Jinan, Shandong 250014, China.
  • Chongxuan Tian
    School of Control Science and Engineering, Shandong University, Jinan, Shandong, 250061, China.
  • Wen Liu
    Department of Dermatology, Air Force General Hospital, PLA Beijing 100142, China.
  • Yang Li
    Occupation of Chinese Center for Disease Control and Prevention, Beijing, China.
  • Wei Li
    Department of Nephrology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
  • Zunsong Wang
    Department of Nephrology, Shandong Institute of Nephrology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, No. 16766 Jingshi Road, Jinan, Shandong 250014, China. Electronic address: wzsong3@163.com.

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