2019冠状病毒病大流行期间的认知医疗物联网、医疗大数据分析和基于人工智能的诊断算法

Michael Lăzăroiu George Morrison
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引用次数: 10

摘要

(Rathore et al., 2020)随着基于物联网的智能医疗保健系统和云计算的进步,廉价的卫生服务和相关支持,集中管理的一致监管(l等,2021)和公共卫生监测可以进行。研究设计、调查方法和材料访谈是在线进行的,数据采用人口普查局美国社区调查的五个变量(年龄、种族/民族、性别、教育程度和地理区域)加权,以可靠和准确地反映美国的人口构成。(Ismail et al., 2020)通过基于物联网的医疗植入物和可穿戴设备,实时远程监控应用可以减少临床就诊和医院护理。(Santagati et al., 2020)医疗物联网阐明了智能医疗设备和软件应用的网络化基础设施,确保数据存储在云平台上,并在预防和跟踪慢性疾病的同时实现准确诊断。
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Cognitive Internet of Medical Things, Big Healthcare Data Analytics, and Artificial intelligence-based Diagnostic Algorithms during the COVID-19 Pandemic
(Rathore et al., 2020) With the advancement of Internet of Thingsbased smart healthcare systems and cloud computing, inexpensive health services and associated support, coherent regulation of the centralized administration (Lăzăroiu et al., 2021), and public health monitoring can be carried out. Study Design, Survey Methods, and Materials The interviews were conducted online and data were weighted by five variables (age, race/ethnicity, gender, education, and geographic region) using the Census Bureau's American Community Survey to reflect reliably and accurately the demographic composition of the United States. (Ismail et al., 2020) Real-time remote monitoring applications, through Internet of Things-based medical implants and wearable devices, can decrease clinical visits and hospital care. (Santagati et al., 2020) Internet of Medical Things articulates the networked infrastructure of smart healthcare devices and software applications, ensuring data storage on cloud platforms and leading to accurate diagnoses while preventing and tracking chronic illnesses.
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