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Smart Biomedical Sensors, Big Healthcare Data Analytics, and Virtual Care Technologies in Monitoring, Detection, and Prevention of COVID-19
American Journal of Medical Research ; 8(1):60-70, 2021.
Article in English | ProQuest Central | ID: covidwho-1181953
ABSTRACT
Keywords COVID-19;big healthcare data analytics;virtual care technology 1.Introduction Fortified by big healthcare data analytics and smart biomedical sensors, artificial intelligence-powered systems can supply information as regards resource deployment in various regions, offering suggestions on system redeployment and clinician involvement during the COVID-19 pandemic by use of virtual care technologies. (Wittenberg et al., 2021) 2.Conceptual Framework and Literature Review For patients not infected with COVID-19, particularly persons at significant risk of being affected (e.g., older individuals having prior medical conditions), telehealth can deliver readily available access to standard care without exposure in an overcrowded facility or in medical practice waiting rooms. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate. 4.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. (Kumar et al., 2021) Internet of Medical Things can be integrated with clinical practice by leveraging streamlined predictive models and algorithms advanced by use of approaches of bioinformatics to identify and inspect wide-ranging various datasets, comprising clinical big data, to harness disease-risk forecast and prognosis to further personalized medicine.
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Collection: Databases of international organizations Database: ProQuest Central Language: English Journal: American Journal of Medical Research Year: 2021 Document Type: Article

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Collection: Databases of international organizations Database: ProQuest Central Language: English Journal: American Journal of Medical Research Year: 2021 Document Type: Article