Forecasting and Prediction of COVID-19 Severity Using Machine Learning and Time-Series Models

Assistant Professor ISE Dept SJCIT Chickballapur, India
Professor CSE Dept PESITM Shivamogga, India

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Abstract

It's great to see the use of data science and deep learning algorithms being applied to important real-world problems like identifying COVID-19 in medical images and forecasting the number of deaths due to COVID-19. The use of image segmentation with VGG16 classifier is a powerful technique to detect defects in scanned images, and the ability to classify CT images into COVID and non-COVID classes is a valuable tool for medical professionals in diagnosing the disease. The forecasting system described, which uses linear regression and Fbprophet models to predict the number of deaths due to COVID-19, is also a valuable contribution to the field. By providing accurate predictions of the impact of COVID-19 on lung health, governments and medical professionals can better prepare for and respond to the ongoing pandemic. Overall, the work described demonstrates the potential of data science to make a positive impact on society by providing insights and solutions to important real- world problems.