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Internet of things sensor assisted security and quality analysis for health care data sets using artificial intelligent based heuristic health management system

机译：事物互联网传感器使用人工智能的启发式健康管理系统辅助保健数据集的安全和质量分析

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The developments in the medical systems, especially in health care management systems, play a vital role in patients. The effective management of health records leads to an increase in the importance of the healthcare management system all over the world. A real-time health monitoring system is a key zone for the Internet of Things (IoT) sensor technology in human services using Big Data Analytics. The major challenge that has to do with the health care data sets is security and privacy. In this paper, an artificial intelligence-based heuristic health management system has been designed and developed. This system is exceptionally close to improve the security and privacy of the live datasets of patients and the association of medicinal services over its different viewpoints. These services include the capacity for specialists, experts, attendants, and staff to settle on better decisions faster. Moreover, security and quality of data by configuration should be a part of any IoT use case, task or arrangement. Utilizing IoT assisted artificial intelligent based heuristic health management system intends to improve and minimize the security risk on health care data sets with assisted IoT sensors. The experimental results show promising outcomes in terms of various performance factors. The system attains precision as 99.75%, error rate as 0.0646 and predicted positive condition rate as 98.46%, Informedness as 98.6% and accuracy as 99.66%. The system is implemented using the MATLAB program. (C) 2020 Elsevier Ltd. All rights reserved.
机译：医疗系统的发展，特别是在医疗保健管理系统中，对患者发挥至关重要的作用。健康记录的有效管理导致了世界各地医疗保健管理系统的重要性。实时健康监测系统是使用大数据分析的人类服务中的物联网（物联网）传感器技术的关键区域。与医疗保健数据集有关的主要挑战是安全性和隐私。在本文中，设计和开发了一种人工智能的启发式健康管理系统。该系统特别接近，提高患者实时数据集的安全性和隐私以及在其不同观点上的药物服务协会。这些服务包括专家，专家，服务员和工作人员的能力更快地定位。此外，配置的数据安全性和质量应该是任何IOT使用案例，任务或安排的一部分。利用物联网协助人工智能的启发式健康管理系统打算通过辅助物联网传感器来改进和最大限度地减少医疗保健数据集的安全风险。实验结果表明了各种性能因素方面的有希望的结果。该系统达到99.75％，误差率为0.0646，预测阳性条件率为98.46％，知情证为98.6％，准确为99.66％。系统使用MATLAB程序实现。 （c）2020 elestvier有限公司保留所有权利。

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