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

IF 1.7 4区医学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computer Methods in Biomechanics and Biomedical Engineering Pub Date : 2025-04-01 Epub Date: 2024-01-09 DOI:10.1080/10255842.2023.2301414

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

引用次数: 0

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.

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利用单一膀胱内压力信号建立基于 CNN 的儿童膀胱顺应性诊断模型。

膀胱顺应性评估是诊断膀胱功能障碍的关键，而尿动力学检查（UDS）是主要的评估方法。然而，儿童尿动力学检查的应用复杂且耗时。因此，有必要在 UDS 之前开发一种高效的膀胱顺应性筛查方法。在这项研究中，我们构建了一个基于 UDS 的数据集，并设计了一个 1D-CNN 模型来优化和训练网络。然后将训练好的模型应用于仅通过拟议的灌注实验获得的数据集。我们的模型优于其他算法。结果表明，我们的模型具有准确、高效地预警异常膀胱顺应性的潜力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Computer Methods in Biomechanics and Biomedical Engineering 工程技术-工程：生物医学

CiteScore

4.10

自引率

6.20%

发文量

179

审稿时长

4-8 weeks

期刊介绍： The primary aims of Computer Methods in Biomechanics and Biomedical Engineering are to provide a means of communicating the advances being made in the areas of biomechanics and biomedical engineering and to stimulate interest in the continually emerging computer based technologies which are being applied in these multidisciplinary subjects. Computer Methods in Biomechanics and Biomedical Engineering will also provide a focus for the importance of integrating the disciplines of engineering with medical technology and clinical expertise. Such integration will have a major impact on health care in the future.