chunk1

ABSTRACT. Based on an in-depth survey of the literature, the purpose of the paper is to explore virtualized care systems, wearable sensor-based devices, and real-time medical data analytics in COVID-19 patient health prediction. Using and replicating data from Accenture, Amwell, CB Insights, Deloitte, Ericsson ConsumerLab, Kyruus, McKinsey, and Sykes, we performed analyses and made estimates regarding how smart technologies can monitor the patients confirmed with COVID-19. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate.

Keywords: COVID-19; medical data analytics; virtual care; patient health prediction

How to cite: Parker, R., Strakova, E., and Janikova, J. (2021). “Virtualized Care Systems, Wearable Sensor-based Devices, and Real-Time Medical Data Analytics in COVID-19 Patient Health Prediction,” American Journal of Medical Research 8(1): 50–59. doi: 10.22381/ajmr8120215.

Received 13 December 2020 • Received in revised form 20 February 2021
Accepted 23 February 2021 • Available online 28 February 2021

Rebecca Parker
This email address is being protected from spambots. You need JavaScript enabled to view it.
The Center for Real-Time and Remote
Health Monitoring Internet of Things-based
Systems at AAER, Auckland, New Zealand
(corresponding author)
Eliska Strakova
This email address is being protected from spambots. You need JavaScript enabled to view it.
The School of Expertness and Valuation,
The Institute of Technology and Business
in Ceske Budejovice, Czech Republic
Jana Janikova
This email address is being protected from spambots. You need JavaScript enabled to view it.
The School of Expertness and Valuation,
The Institute of Technology and Business
in Ceske Budejovice, Czech Republic

Home | About Us | Events | Our Team | Contributors | Peer Reviewers | Editing Services | Books | Contact | Online Access

© 2009 Addleton Academic Publishers. All Rights Reserved.

 
Joomla templates by Joomlashine