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Intelligent health monitoring system modeling based on machine learning and agent technology

机译：基于机器学习和代理技术的智能健康监控系统建模

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摘要

The use of machine learning approach in the field of health informatics improves the quality and effectiveness of decision-making process. Its particular integration into the Remote Health Monitoring Systems (RHMS) allows: collecting, analyzing and learning from real-time data, automatically gaining knowledge and making predictions on the patients state. The RHMS represent an effective solution to control and monitor a growing number of dependent or elderly patients. They showed impressive results in healthcare applications. These systems are built around the sensors installed on the body of the patient and others embedded in their environments. In this context, we are confronted with the challenge of temporal aspect of data. To meet this challenge, we propose that RHMS combine machine learning for generating intelligent valuable information, and visual analytics for gaining insight the collected real-time data. The success of these applications is based on the quality of their design and development. For this reason, we propose to design a RHMS using multi-agent technology. The developed prototype was evaluated to verify our proposal feasibility.
机译：在卫生信息学领域使用机器学习方法提高了决策过程的质量和有效性。其特殊集成到远程健康监测系统（RHM）允许：从实时数据中收集，分析和学习，自动获得知识和对患者状态的预测。 RHM表示控制和监测越来越多的依赖或老年患者的有效解决方案。他们在医疗保健应用中表现出令人印象深刻的结果。这些系统围绕安装在患者身体的传感器和嵌入在其环境中的其他系统。在这种情况下，我们面临着数据的临时方面的挑战。为满足这一挑战，我们建议RHMS结合机器学习，以产生智能有价值的信息，以及用于获得所收集的实时数据的洞察力的视觉分析。这些应用程序的成功基于其设计和开发的质量。因此，我们建议设计使用多种代理技术的RHM。评估开发的原型以验证我们的建议可行性。

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  • 来源
    《Multiagent and grid systems》 |2020年第2期|207-226|共20页
  • 作者

    Elouni Jihed; Ellouzi Hamdi; Ltifi Hela; Ayed Mounir Ben;

  • 作者单位

    Research Groups in Intelligent Machines University of Sfax National School of Engineers;

    Research Groups in Intelligent Machines University of Sfax National School of Engineers;

    Research Groups in Intelligent Machines University of Sfax National School of Engineers|b Computer Sciences and Mathematics Department Faculty of Sciences and Techniques of SidiBouzid University of Kairouan;

    Research Groups in Intelligent Machines University of Sfax National School of Engineers|c Computer Sciences and Communication Department Faculty of Sciences of Sfax University of Sfax;

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  • 原文格式 PDF
  • 正文语种 eng
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  • 关键词

    Remote health monitoring system; machine learning; visualization; data mining; multi-agent system;

    机译：远程健康监控系统;机器学习;可视化;数据挖掘;多智能体系;

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