Wearable Medical Sensor Devices, Machine and Deep Learning Algorithms, and Internet of Things-based Healthcare Systems in COVID-19 Patient Screening, Diagnosis, Monitoring, and Treatment

Keywords: Internet of Things;wearable medical sensor device;COVID-19 1.Introduction The purpose of my systematic review is to examine the recently published literature on COVID-19 patient screening, diagnosis, monitoring, and treatment, and integrate the insights it configures on wearable medical sensor devices, machine and deep learning algorithms, and Internet of Things-based healthcare systems. The identified gaps advance how smart healthcare services are essential in remote patient monitoring through medical data storage, transfer, sharing, processing, collection, and analysis. The manuscript is organized as following: theoretical overview (section 2), methodology (section 3), machine learning algorithms in COVID-19 patient screening, diagnosis, monitoring, tracking, and treatment (section 4), wireless wearable healthcare networks and smart mobile devices in Internet of Medical Things (section 5), smart healthcare services in remote patient monitoring (section 6), discussion (section 7), synopsis of the main research outcomes (section 8), conclusions (section 9), limitations, implications, and further directions of research (section 10). Taking into account the physiological features of people, distinct treatment replications through medical sensor devices can be performed to evaluate the health risk and establish exemplary medical procedures.