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

Gang Yuan, Zicong Ge, Jian Zheng, Xiangming Yan, Mingcui Fu, Ming Li, Xiaodong Yang and Liangfeng Tang

Computer Methods in Biomechanics and Biomedical Engineering, 2025, vol. 28, issue 5, 698-709

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.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/10255842.2023.2301414 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:gcmbxx:v:28:y:2025:i:5:p:698-709

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/gcmb20

DOI: 10.1080/10255842.2023.2301414

Access Statistics for this article

Computer Methods in Biomechanics and Biomedical Engineering is currently edited by Director of Biomaterials John Middleton

More articles in Computer Methods in Biomechanics and Biomedical Engineering from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().