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在医疗应用中使用人工神经网络对分泌生物进行比较识别研究

Shitharth Selvarajan¹, Hariprasath Manoharan², Celestine Iwendi³

¹Department of Computer Science, Kebri Dehar University, Kebri Dehar, Ethiopia.

Frontiers in bioengineering and biotechnology

|July 3, 2023

概括

这项研究引入了一个带有神经网络的无线传感器系统,用于监测老年人的消化健康,将数据丢失减少到1.39%,并将监测效率提高了68%.

科学领域:

生物医学工程生物医学工程
医疗信息学医疗信息学
老年学是一门学科.

背景情况:

消化系统疾病在老年人群中很普遍.
目前的监测方法在预防严重并发症方面可能存在局限性.

研究的目的:

为内部消化系统开发先进的参数监测系统.
通过早期检测和干预,预防老年人严重的胃肠道问题.

主要方法:

实现一个无线传感器网络进行参数监控.
集成一个神经网络来分析监控的参数.
制定控制行动,以减轻胃肠道活动和减少数据丢失.

主要成果:

拟议的系统在无线传感器网络监控期间实现了1.39%的优化数据损失.
基于四个分析案例的评估确定了控制参数和重量机构.
在参数评估中,该系统的有效率比对照病例高68%.

结论:

神经网络集成显著提高了消化系统监测的有效性.
开发的系统有效地减少了数据丢失,并提高了老年人胃肠道问题的检测率.

关键词:

攻击攻击攻击攻击控制参数的控制参数消化系统的消化系统.这是一个损失,损失损失.神经网络的神经网络的神经网络

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