Artificial Intelligence Enabled Dual Diagnostic Based Algorithm For The Detection Of COVID-19 Patients

Abstract

COVID-19, a global pandemic first surfaced in the city of Wuhan, China and has henceforth transcended differently across geographical borders, classes, and genders from different age groups, sometimes mutating its own DNA strands in the process as well. Hospitals and medical centres are getting overburdened by the sheer magnitude of the spread of the pandemic. While IoT in healthcare had already dominated the public discourse, the onset of COVID-19 has been a watershed development. The need of the hour is to deploy robots and IoT devices to keep a check on patient’s body vitals, as well as monitor their other pathological data to further have a control on the spread. Needless to mention, there has never been a more urgent reason as today to mobilize digital innovations for providing healthcare services remotely through computing devices and patient-facing artificial intelligence (AI) powered medical aids. In this paper our group has developed an AI enabled Decision Support System for automating the entire process flow from estimation to detection of COVID-19 subjects as part of an Intelligent Value Chain algorithm for the first time. The proposed method is validated and computational complexity is estimated in different Single Board Computer (SBC) platform. The NVIDIA Xavier CUDA system provides very low training and predicted time when compared to raspberry pi-4 and Jetson Nano.