ABSTRACT. We draw on a substantial body of theoretical and empirical research on cognitive Internet of Medical Things, big healthcare data analytics, and artificial intelligence-based diagnostic algorithms during the COVID-19 pandemic, and to explore this, we inspected, used, and replicated survey data from Brookings, CB Insights, Ericsson ConsumerLab, Gartner, McKinsey, and Sykes, performing analyses and making estimates regarding Internet of Medical Things-related diagnosis, prognosis, and treatment. Internet of Medical Things furthers healthcare systems considerably, optimizing processes that enable cutting-edge diagnosis and treatment methods through interconnected wearable sensor devices and real-time monitoring data acquired through Internet of Things technologies. Wearable devices, Internet of Things-based smart health monitoring, and artificial intelligence-based diagnosis can swiftly identify or predict possible COVID-19 patients. Artificial intelligence-enabled wearable medical devices facilitate remote monitoring processes. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate.

Keywords: Internet of Medical Things; COVID-19; big healthcare data analytics

How to cite: Morrison, M., and Lăzăroiu, G. (2021). “Cognitive Internet of Medical Things, Big Healthcare Data Analytics, and Artificial intelligence-based Diagnostic Algorithms during the COVID-19 Pandemic,” American Journal of Medical Research 8(2): 23–36. doi: 10.22381/ajmr8220212.

Received 17 May 2021 • Received in revised form 14 October 2021
Accepted 19 October 2021 • Available online 28 October 2021

Michael Morrison
This email address is being protected from spambots. You need JavaScript enabled to view it.
The Center for Medical Big Data Analytics
at AAER, Calgary, Canada
George Lăzăroiu
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The Institute of Smart Big Data Analytics,
New York City, NY, USA;
Spiru Haret University, Bucharest, Romania
(corresponding author)

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