Internet of Medical Things-based Clinical Decision Support Systems, Smart Healthcare Wearable Devices, and Machine Learning Algorithms in COVID-19 Prevention, Screening, Detection, Diagnosis, and Treatment
Roman Blazek1, Lenka Hrosova1, and Janet Collier2ABSTRACT. We draw on a substantial body of theoretical and empirical research on Internet of Medical Things-based clinical decision support systems, smart healthcare wearable devices, and machine learning algorithms in COVID-19 prevention, screening, detection, diagnosis, and treatment. With increasing evidence of wearable Internet of Medical Things technologies, there is an essential demand for comprehending whether tracking infected patients by machine learning algorithms can prevent the spread of COVID-19 by processing and analyzing accurate data. In this research, prior findings were cumulated indicating that Internet of Medical Things-assisted cutting-edge biosensor technologies are pivotal in COVID-19 infection. We carried out a quantitative literature review of ProQuest, Scopus, and the Web of Science throughout February 2022, with search terms including “COVID-19” + “Internet of Medical Things-based clinical decision support systems,” “smart healthcare wearable devices,” and “machine learning algorithms.” As we analyzed research published in 2021 and 2022, only 141 papers met the eligibility criteria. By removing controversial or unclear findings (scanty/unimportant data), results unsupported by replication, undetailed content, or papers having quite similar titles, we decided on 25, chiefly empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Distiller SR, ROBIS, and SRDR.
Keywords: smart healthcare wearable device; COVID-19; Internet of Medical Things
How to cite: Blazek, R., Hrosova, L., and Collier, J. (2022). “Internet of Medical Things-based Clinical Decision Support Systems, Smart Healthcare Wearable Devices, and Machine Learning Algorithms in COVID-19 Prevention, Screening, Detection, Diagnosis, and Treatment,” American Journal of Medical Research 9(1): 65–80. doi: 10.22381/ajmr9120225.
Received 28 February 2022 • Received in revised form 24 April 2022
Accepted 26 April 2022 • Available online 30 April 2022
