Accurate classification of glomerular diseases by hyperspectral imaging and transformer.

Journal: Computer methods and programs in biomedicine
PMID: 38964248

Abstract

BACKGROUND AND OBJECTIVE: In renal disease research, precise glomerular disease diagnosis is crucial for treatment and prognosis. Currently reliant on invasive biopsies, this method bears risks and pathologist-dependent variability, yielding inconsistent results. There is a pressing need for innovative diagnostic tools that enhance traditional methods, streamline processes, and ensure accurate and consistent disease detection.

Authors

  • Chongxuan Tian
    School of Control Science and Engineering, Shandong University, Jinan, Shandong, 250061, China.
  • Yuzhuo Chen
    School of Control Science and Engineering, Shandong University, Jinan, Shandong, 250061, China.
  • Yelin Liu
    Zolix Instruments Co. Ltd., 16 Huanke Middle Road, Tongzhou District, Beijing 101102, China.
  • Xin Wang
    Key Laboratory of Bio-based Material Science & Technology (Northeast Forestry University), Ministry of Education, Harbin 150040, China.
  • Qize Lv
    School of Control Science and Engineering, Shandong University, Qianfoshan Campus, 17923 Jingshi Road, Jinan, Shandong 250061, China.
  • Yunze Li
    School of Control Science and Engineering, Shandong University, Qianfoshan Campus, 17923 Jingshi Road, Jinan, Shandong 250061, China.
  • Jinlin Deng
    School of Control Science and Engineering, Shandong University, Qianfoshan Campus, 17923 Jingshi Road, Jinan, Shandong 250061, China.
  • Yifei Liu
    College of Data Science, Taiyuan University of Technology, Taiyuan, Shanxi, China.
  • Wei Li
    Department of Nephrology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.

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