Analysis Of Covid-19 Using Chest X-Ray Images: An AI Based Prospective

The unprecedented surge of Disease occurred in 2019, December named under covid-19, also known as corona-virus, was responsible for outbreaks happening in 2019–2020. It was first diagnosed in Wuhan, Hubei Province in the country China. Coronavirus is phenotypically and genotypically diverse in its behavior. Further, confirmed worldwide cases on April 6, 2020, consisting of 12,11,214 cases reported to the World Health Organization (WHO). The reverse-transcript-ase polymer-ase chain reaction (RT-PCR) is the common solution utilized in the recognition of coronavirus, which has been found to be time-consuming and troublesome. On February 14, 2020, the laboratory-confirmed cases were 49,053 and deaths including 1,381 were documented. As of August 12, 2020, the virus has afflicted the lives of 20,674,903 people. It shows that deadly diseases are surging, plunging, and scattering illiberally in the current world. In accordance with the World Health Organization (WHO), over and above, 30 peculiar diseases like SARS coronavirus (SARS-COV), MERS coronavirus (MERS-COV), and H1N1 influenza, etc., have been diagnosed in previous twenty years to affect the health fitness situation of billions of people. The prime objective of this article is to make a review paper with artificial intelligence as a primary objective. It takes all the research to draw the comparative analyses of the distinct characteristics of data, mainly x-ray images of the chest, providing technologies and approaches to detect and prognosis coronavirus with learning algorithms. With the aim of finding the best-suited model, we compared the research on the basis of essential factors such as size of the batch , rate of learning, summed epochs till which it runs, and nature of optimizer.