Medical Big Data and Wearable Internet of Things Healthcare Systems in Remotely Monitoring and Caring for Confirmed or Suspected COVID-19 Patients
Medical Big Data and Wearable Internet of Things Healthcare Systems in Remotely Monitoring and Caring for Confirmed or Suspected COVID-19 Patients

Summary/Abstract: The purpose of this study was to empirically examine medical big data and wearable Internet of Things healthcare systems in remotely monitoring and caring for confirmed or suspected COVID-19 patients. Building our argument by drawing on data collected from Accenture, Amwell, Deloitte, Ericsson ConsumerLab, Kyruus, The Rockefeller Foundation, Syneos Health, and USAID, we performed analyses and made estimates regarding artificial intelligence-driven biosensors in diagnosis, surveillance, and prevention during the COVID-19 pandemic. Artificial intelligence-powered diagnostic tools have been instrumental in COVID-19 prevention, screening, and treatment. Internet of Medical Things enables medical data sharing essential in disease diagnosis and treatment. Deep machine learning and cloud computing are pivotal in Internet of Things-based healthcare. Internet of Medical Things systems enable remote patient monitoring as regards chronic diseases. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate.

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