Polynomial Based Linear Regression Model to Predict COVID-19 Cases

Abstract

The epidemic COVID-19 has profoundly influenced people's wellness worldwide and the number of fatalities from diseases continues to increase world-wide. Despite technology's remarkable success in our daily lives, notably in ML and DL, AI also helped humanity fight the grueling COVID-19 war. DL is only one approach of ensuring that potential data-driven technologies can help humankind manage COVID-19. Big data and artificial intelligence are used to leverage exceptional efforts to combat the COVID-19 pandemic crisis. In some prior disease outbreaks, various AI offshoots were deployed. AI was applied in the identification of disease clusters, case monitoring, future outbreak predictions, mortality risk, and diagnosis of COVID-19, resource allocation illness management, training facilitation, record maintaining and design identification for the investigation of the trend towards the illness. AI Machine learning can help to find out the strategies to prevent the Corona virus. This paper presents a polynomial based linear regression model to predict the future cases according to the current situation using data of last few months, showing the output on the graph. The paper also discusses the applications of AI Machine learning in Corona virus pandemic like forecasting infection rate, diagnose with images comprehensively and will also discuss the role of Machine learning in facilitating the development of vaccine as well.