Prediction of COVID-19 using Convolution Neural Network

Convolutional Neural Networks (CNN) and Machine Learning (ML) have evolved a long way in the modern technological era. They are used in analysis and prediction of various segments of normal life. They have a greater advantage when it comes to understanding a process, sometimes even better than a human brain. The Virus that is generated as COVID-19 is mainly caused when a person coughs, sneeze or exhales and it is transmitted as a small particle to other bodies and form these viruses. One of the major tricks for stopping the spread of this covid-19 is social distancing and rapid testing. This rapid test will take 2-3 days of time to get the result of covid-19. This may trouble a large amount of people in terms of money and time. Therefore, with the advantage of CNN, devised a method to increase the efficiency of the testing process. X-rays and CT scans show considerable advantage in detecting COVID-19 in a person. COVID-19 affects the lungs primarily which could be caught in X-rays as a white overlay. Constructed a model that could identify whether the submitted X-ray is of a normal person or of a COVID-19 positive person.

Autorentext

Dr. Prathibhavani P. M. Arbeitet derzeit als Assistenzprofessor in der Abteilung für CSE, UVCE, K R Circle, Bengaluru, Bangalore University.Sie promovierte in CSE an der VTU. Sie verfügt über mehr als 13 Jahre Unterrichtserfahrung. Sie hat mehr als 22 Fachbeiträge im Bereich WSN veröffentlicht. Sie ist lebenslanges Mitglied von IAENG, ISTE.