Identifying COVID-19 in chest X-ray and CT scan images through the application of machine learning algorithms.

Abstract

Since the beginning of the current COVID-19 pandemic, more than five million people have been infected and the numbers are still on the rise. Early symptom detection and proper hygienic standards are thus of utmost importance, especially in venues where people are in random or opportunistic contact with each other. To this end, automated systems with medical-grade body temperature measurement, hygienic compliance evaluation and individualized, person-to-person tracking, are essential, not only for disease spread intervention and prevention, but also to assure economic stability. Herein, we present a system that encapsulates all of the mentioned functionality via readily-available components (both hardware and software) and is further enhanced with preliminary RTLS data acquisition, enabling post-symptom detected, person-to person interaction identification to asses’ potential infection vectors and mitigate further propagation thereof by means of smart quarantine.