Detection of COVID-19 using CNN's Deep Learning Method: Review

Abstract

cOVID-19 is a global pandemic that occurred in March 2020. COVID-19 spreads very quickly because it is an infectious disease. COVID-19 has similar characteristics to Pneumonia. The X-Ray results of COVID-19 and Pneumonia can also be said to be similar, making it difficult to distinguish. The object of detection is beneficial to the medical community, especially radiologists, who utilize it to diagnose patients with COVID-19. COVID-19 can be found by using X-Ray images in the medical field. In detecting COVID-19, there are usually many methods that can be used, one of which is deep learning. Convolutional Neural Network (CNN) is a Deep Learning model that can be used to detect images. This research examines previous research on the detection of COVID-19 using CNN's Deep Learning Method, many existing models for COVID-19 detection studies, and some researchers-built models using CNN's Deep Learning Method. The study shows that CNN's Deep Learning accurately detects COVID-19, Negative COVID-19, and Pneumonia. The Multi-layered CNN model uses 3.990 X-Ray images and offers good accuracy, sensitivity, and specificity