ABSTRACT. Despite the relevance of smart healthcare devices and applications, machine learning-based automated diagnostic systems, and real-time medical data analytics in COVID-19 screening, testing, and treatment, only limited research has been conducted on this topic. Using and replicating data from Canada Health Infoway, CBRE, Doximity, Leger, McKinsey, Mercer, PwC, R2G, and Sykes, we performed analyses and made estimates regarding real-time patient monitoring and biomedical big data in Internet of Things-enabled health care. Artificial intelligence-powered tools are instrumental in COVID-19 diagnosis and screening. Smart Internet of Medical Things devices are networked to gather multimodal patient data throughout remote health monitoring. Wearable sensors interconnected across net- worked devices can produce data that assist in care process automation. COVID-19 detection and monitoring systems can be put into action throughout an Internet of Medical Things infrastructure. The results of a study based on data collected from 6,400 respondents provide support for our research model. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate.

Keywords: COVID-19; smart healthcare; medical data analytics; remote monitoring

How to cite: Stanley, A., and Kucera, J. (2021). “Smart Healthcare Devices and Applications, Machine Learning-based Automated Diagnostic Systems, and Real-Time Medical Data Analytics in COVID-19 Screening, Testing, and Treatment,” American Journal of Medical Research 8(2): 105–117. doi: 10.22381/ajmr8220218.

Received 16 May 2021 • Received in revised form 13 October 2021
Accepted 17 October 2021 • Available online 28 October 2021