The novel coronavirus infection (COVID-19) that was first identified in China in December 2019 has spread across the globe rapidly infecting over ten million people. The World Health Organization (WHO) declared it as a pandemic on March 11, 2020. What makes it even more critical is the lack of vaccines available to control the disease, although many pharmaceutical companies and research institutions all over the world are working toward developing effective solutions to battle this life-threatening disease. X-ray and computed tomography (CT) images scanning is one of the most encouraging exploration zones; it can help in finding and providing early diagnosis to diseases and gives both quick and precise outcomes. In this study, convolution neural networks method is used for binary classification pneumonia-based conversion of VGG-19, Inception_V2 and decision tree model on X-ray and CT scan images dataset, which contains 360 images. It can infer that fine-tuned version VGG-19, Inception_V2 and decision tree model show highly satisfactory performance with a rate of increase in training and validation accuracy (91%) other than Inception_V2 (78%) and decision tree (60%) models. Keywords COVID-19 Á X-ray images Á CT scan Á CNN Á VGG-16 Á Inception_V2 Á Decision tree 1 Introduction The first case of the virus became exposed in Wuhan city of China in November 2019, there are 1,100,000 peoples living in this city and it interfaces numerous urban communities of China. The outbreak of atypical and individual-to-individual transmissible pneumonia brought about by the severe acute respiratory syndrome coronavirus-2 (SARS-COV-2) has caused a worldwide. There have been in excess of 26,000,000 confirmed cases of the corona virus disease (COVID-19) on the globe, as of April 23, 2020. As indicated by the WHO, 16-21% of individuals with the infection have gotten seriously sick with a Communicated by Valentina E. Balas.

The forecasting model used random forest algorithm. From the outcomes, it has been found that the regression models utilize basic linkage works and are exceptionally solid for forecast of COVID-19 cases in different countries as well as India. Current shared of worldwide COVID-19 confirmed case has been predicted by taking the world population and a comparatives study has been done on COVID-19 total cases growth for top 10 worst affected countries including US and excluding US. The ratio between confirmed cases vs. fatalities of COVID-19 is predicted and in the end a special study has been done on India where we have forecasted all the age groups affected by COVID-19 then we have extended our study to forecast the active, death and recovered cases especially in India and compared the situation with other countries.