ABSTRACT
As the Covid-19 puts the great impact on the world health and economic situations, which directly leads toward the crisis. Prediction helps us to take precaution accordingly. Currently, more than 293 million of positive cases have been detected and more than 5.4 million deaths have been recorded. To prevail the spread of virus many countries open sourced datasets of Covid-19 positive cases for scientists to predict the curve. Therefore, countries can take the measures accordingly. It helps to obtain a rough idea about the pandemic end date, which is very difficult to predict because of its uncertainty. This article takes the dataset of many countries and predicts the curve of positive cases of the top 10 countries. We used this data to integrate it with logistic regression model to have a future view of pandemic. The article consists of two parts. First part includes the prediction by using logistic regression. This function used Python programming, Panda's machine learning library, whereCovid-19 dataset has been taken from the open-source dataset available on the internet. Second part includes the detection of Covid-19 using Deep Learning Convolution neural network method. CNN method is used by training the model with the dataset of X-ray Images. CNN can detect the virus at early stages because of its powerful deep learning multiple layers ‘algorithm. There are several stages of detection such as processing image datasets and applying image-processing techniques to have a clear understanding of features in X-ray images. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.