A Classification Application Based on Support Vector Machine for Health IoT

Su Caiyu, Dong Jie, Mo Yi, Wu Shanyun
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引用次数: 1

Abstract

The booming socio-economic development has led to great progress in the Internet of Things (IoT) and computer technology, which are gradually applied in all aspects of society. The Internet of Health Things (IoH) has emerged to meet the new era of higher demands placed on medical institutions. Machine learning is beginning to be used in the medical service system and is achieving significant results in driving related services. This paper analyses sensor data from several elderly people to analyse their postural status and text reports on classification metrics. The performance of the support vector machine on this problem is evaluated using information such as accuracy, recall, and F1 value. The study achieves a more accurate judgement of the health status of the elderly and provides some help to medical institutions in developing relevant treatment plans, as well as providing a reference for related academic research. abstract
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基于支持向量机的健康物联网分类应用
随着社会经济的蓬勃发展,物联网和计算机技术取得了长足的进步,并逐渐应用于社会的各个方面。健康物联网(IoH)应运而生,以满足对医疗机构提出更高要求的新时代。机器学习正在开始应用于医疗服务系统,并在驱动相关服务方面取得了显著成果。本文分析了几位老年人的传感器数据,分析了他们的姿势状态和分类指标的文本报告。支持向量机在这个问题上的性能是使用诸如准确率、召回率和F1值等信息来评估的。本研究实现了对老年人健康状况更准确的判断,为医疗机构制定相关治疗方案提供一定帮助,同时也为相关学术研究提供参考。摘要
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