COVID-X: Novel Health-Fog Framework Based on Neutrosophic Classifier for Confrontation Covid-19

COVID-X: Novel Health-Fog Framework Based on Neutrosophic Classifier for Confrontation Covid-19

Ibrahim Yasser, Abeer Twakol, A. A. Abd El-Khalek, Ahmed Samrah, A. A. Salama

The newly identified Coronavirus pneumonia, subsequently termed COVID-19, is highlytransmittable and pathogenic with no clinically approved antiviral drug or vaccine available fortreatment. Technological developments like edge computing, fog computing, Internet of Things(IoT), and Big Data have gained importance due to their robustness and ability to provide diverseresponse characteristics based on target application. In this paper, we present a novel Health-Fogframework universal system to automatically assist the early diagnosis, treatment, and preventiveof people with COVID-19 in an efficient manner. Achieving an empirical of the proposed frameworkwhich mix between deep learning and Neutrosophic classifiers in the task of classifying COVID-19.There are some proposed applications based on the proposed COVID-X framework such as smartmask, smart medical suit, safe spacer, and Medical Mobile Learning (MML) will be presented.Computer-aided diagnosis systems could assist in the early detection of COVID-19 abnormalitiesand help to monitor the progression of the disease, potentially reduce mortality rates.

2020

coronavirus pneumonia; covid-19; intelligent medical system; fog computing; health-fog; neutrosophic; deep learning; computer-aided diagnosis

10.5281/zenodo.3951625

Neutrosophic Sets and Systems

University of New Mexico

Mathematics, Electronic computers. Computer science