Get 20M+ Full-Text Papers For Less Than $1.50/day. Subscribe now for You or Your Team.

Learn More →

Smart Wearable Internet of Medical Things Technologies, Artificial Intelligence-based Diagnostic Algorithms, and Real-Time Healthcare Monitoring Systems in COVID-19 Detection and Treatment

Smart Wearable Internet of Medical Things Technologies, Artificial Intelligence-based Diagnostic... Based on an in-depth survey of the literature, the purpose of the paper is to explore smart wearable Internet of Medical Things technologies, artificial intelligence- based diagnostic algorithms, and real-time healthcare monitoring systems in COVID-19 detection and treatment. In this research, previous findings were cumulated showing that big data analytics can optimize healthcare services in Internet of Medical Things, and we contribute to the literature by indicating that data connectivity and sharing are pivotal in healthcare services. Throughout January 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “COVID-19” + “smart wearable Internet of Medical Things technologies,” “artificial intelligence-based diagnostic algorithms,” and “real-time healthcare monitoring systems.” As research published between 2020 and 2022 was inspected, only 127 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, we selected 31 mainly empirical sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Dedoose, Distiller SR, and SRDR. Keywords: Internet of Medical Things; diagnostic algorithm; COVID-19 How to cite: Crowell, B., Cug, J., and Katarina Michalikova, K. (2022). “Smart Wearable Internet of Medical Things Technologies, Artificial Intelligence-based Diagnostic Algorithms, and Real-Time Healthcare Monitoring Systems in COVID-19 Detection and Treatment,” American Journal of Medical Research 9(1): 17–32. doi: 10.22381/ajmr9120222. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png American Journal of Medical Research Addleton Academic Publishers

Smart Wearable Internet of Medical Things Technologies, Artificial Intelligence-based Diagnostic Algorithms, and Real-Time Healthcare Monitoring Systems in COVID-19 Detection and Treatment

American Journal of Medical Research , Volume 9 (1): 16 – Jan 1, 2022

Loading next page...
 
/lp/addleton-academic-publishers/smart-wearable-internet-of-medical-things-technologies-artificial-AIRNvOYzkS

References

References for this paper are not available at this time. We will be adding them shortly, thank you for your patience.

Publisher
Addleton Academic Publishers
Copyright
© 2009 Addleton Academic Publishers
ISSN
2334-4814
eISSN
2376-4481
Publisher site
See Article on Publisher Site

Abstract

Based on an in-depth survey of the literature, the purpose of the paper is to explore smart wearable Internet of Medical Things technologies, artificial intelligence- based diagnostic algorithms, and real-time healthcare monitoring systems in COVID-19 detection and treatment. In this research, previous findings were cumulated showing that big data analytics can optimize healthcare services in Internet of Medical Things, and we contribute to the literature by indicating that data connectivity and sharing are pivotal in healthcare services. Throughout January 2022, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “COVID-19” + “smart wearable Internet of Medical Things technologies,” “artificial intelligence-based diagnostic algorithms,” and “real-time healthcare monitoring systems.” As research published between 2020 and 2022 was inspected, only 127 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, we selected 31 mainly empirical sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Dedoose, Distiller SR, and SRDR. Keywords: Internet of Medical Things; diagnostic algorithm; COVID-19 How to cite: Crowell, B., Cug, J., and Katarina Michalikova, K. (2022). “Smart Wearable Internet of Medical Things Technologies, Artificial Intelligence-based Diagnostic Algorithms, and Real-Time Healthcare Monitoring Systems in COVID-19 Detection and Treatment,” American Journal of Medical Research 9(1): 17–32. doi: 10.22381/ajmr9120222.

Journal

American Journal of Medical ResearchAddleton Academic Publishers

Published: Jan 1, 2022

There are no references for this article.