Role of Deep Learning in Screening and Tracking of COVID-19

As we head toward more than 34 million cases of Coronavirus disease of 2019 and a million deaths worldwide, there is an urgent need to control the spread and recover the patients as soon as possible. Technology has resolved many complex problems of human beings. Machine learning and deep learning have been intensely used in areas like medical image diagnosis, drug discovery, and manufacturing. It has achieved success in complex problems like the detection of cancerous tumors, skin cancer, and diabetic retinopathy. In this study, considering the power and ability of deep learning, we will study the possibilities and role of deep learning in detecting COVID-19. Several deep learning models can be used to monitor, detect, and predict the spread of the virus. The convolutional neural network has great potential to detect COVID-19 as it is currently used to detect pneumonia using chest X-ray images. This knowledge is used to build a model to detect the presence of COVID-19 which gives a high accuracy with minimum error percentage. The model is highly capable of detecting patients with COVID-19. Deep learning can be implemented widely to tackle this pandemic.