Covid-19 Detection on X-Ray Image Using Deep Learning

An unexpected pandemic known as COVID-19 struck the entire world in the year 2020. Research in numerous sectors has been prompted to address it as a result of the lack of treatment. Understanding the new variety and developing a vaccination become more challenging as a virus evolves. Numerous nations are impacted by the rise of novel variations. Therefore, it is crucial to assess COVID-19's performance in addition to death forecasting. The proposal develops numerous analyses, visualizations, and predictive models that can forecast COVID 19 performance. The goal is to first track data visualization, later Covid 19 data are analyzed and predicted globally to raise awareness by applying machine learning techniques including linear regression, support vector regression, and Holt forecasting method. The objective of this study is to understand how machine learning methods and applications are used for various COVID-19-related tasks and investigations. An analysis of research published in Science Direct, Springer, Hindawi, and MDPI on this topic in 2020 using the search terms COVID-19, machine learning, supervised learning, and unsupervised learning. In total, 16,306 articles were retrieved, but 14 searches from these publications were used in this study. It has been demonstrated that machine learning can be useful for understanding, predicting, and differentiating COVID-19.