Mortality Rate Prediction for COVID-19 Using Machine Learning Technique

Kashyap, V.; Saini, P.; Rabina, Gautam S.

In the present era of pool of technologies, the technical world is drastically shifting to artificial intelligence and all its application areas. One among such unprecedented areas of artificial intelligence is machine learning. Machine learning techniques are way useful for predicting the futuristic results as well as visualizing the data into different form which help the keen researchers and business analysts in determining their study gaps and can achieve the desired outcomes with an ease. With a necessity of well-organized dataset, machine learning algorithms can be implemented on any real-life data such as COVID-19 as it is the most popular topic for researchers today. COVID-19, as per the recent publications, is a pandemic declared by World Health Organization and spreading across the globe at an alarming pace. This has become a threat to human lives due to the reason that no medicine till date has proven its effectiveness to cure the infection spread by COVID-19. The paper is a work on the dataset for COVID-19 in which predictions have been made on the basis of cases emerging in an area and the expected date rate so that the situation can be tackled with all the medical emergency services. Regression is a machine learning technique that has been used for the prediction purpose. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.