Detection of Corona Virus Infection using Convolutional Neural Network

Coronavirus 2019, also known as COVID-19, has recently had a negative influence on public health and human lives. Since the second world war, this disastrous consequence has changed human experience by initiating an increasingly more devastating and unexpected health calamity. The world's condition has become a catastrophic epidemic due to uncontrolled infectious properties within society. Therefore, the initial stage and accurate identification of the virus may be a good strategy for tracking and suppressing the illness from spreading due to the lack of medication. During the pandemic, computed tomography (CT) imaging has been extensively used to detect the percentage of infection. Artificial intelligence-assisted CT- image analysis could be a better option which can be achieved using a convolutional neural network (CNN). This is one of the prominent modes that can be effectively used in such applications. In this paper, an artificial-intelligence-based approach has been presented to investigate the coronavirus infection in the human body. The various experiments are carried out on the freely available dataset. It has been observed that the results are better indicating adequate performance for prediction.