CNN-based diagnosis model of children's bladder compliance using a single intravesical pressure signal.

Journal: Computer methods in biomechanics and biomedical engineering
PMID: 38193146

Abstract

Bladder compliance assessment is crucial for diagnosing bladder functional disorders, with urodynamic study (UDS) being the principal evaluation method. However, the application of UDS is intricate and time-consuming in children. So it'S necessary to develop an efficient bladder compliance screen approach before UDS. In this study, We constructed a dataset based on UDS and designed a 1D-CNN model to optimize and train the network. Then applied the trained model to a dataset obtained solely through a proposed perfusion experiment. Our model outperformed other algorithms. The results demonstrate the potential of our model to alert abnormal bladder compliance accurately and efficiently.

Authors

  • Gang Yuan
    School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230022, China; Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China. Electronic address: yuangang@sibet.ac.cn.
  • Zicong Ge
    School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230022, China; Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China.
  • Jian Zheng
    Biospheric Assessment for Waste Disposal Team, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, 4-9-1 Anagawa, Inage, Chiba 263-8555, Japan; Fukushima Project Headquarters, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, 4-9-1 Anagawa, Inage, Chiba 263-8555, Japan. Electronic address: zheng.jian@qst.go.jp.
  • Xiangming Yan
    Department of Surgery, Children's Hospital of Soochow University, Soochow University, Suzhou, China.
  • Mingcui Fu
    Department of Surgery, Children's Hospital of Soochow University, Soochow University, Suzhou, China.
  • Ming Li
    Radiology Department, Huadong Hospital, Affiliated with Fudan University, Shanghai, China.
  • Xiaodong Yang
    Clinical and Research Center for Infectious Diseases, Beijing Youan Hospital, Capital Medical University, Beijing, China.
  • Liangfeng Tang
    Department of Pediatric Urology, Children's Hospital, Fudan University, Shanghai, 201100, China.

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