Abstract
The evolution of technology creates a rapid effect in every field, whether it is the medical field, research, or any other field. The expedition of the COVID-19or Coronavirus is caused by the SARS-CoV-2 virus in various countries of the world. This infectious disease has affected the whole world in just a matter of no time and it causes millions of deaths. COVID-19 has created a deterrent to public health and which may be considered as one of the greatest pandemic in the world history. Developing a system that can detect Coronavirus disease in humans is a very tough task on the basis of symptoms. By using the concept of machine learning along with ensemble classifier on testing data provide us a better result in the prediction of COVID-19. In this work, our main aim is to develop a predictive model based on the concept of machine learning algorithms which will help us to provide a better way for determining the health risk and predict the risk of COVID-19. In this paper, we have used a dataset of more than 5434 COVID-19 patients. We have also considered different attribute values to determine the disease in early stages. The results demonstrated 97.88% overall accuracy in predicting the occurrence of disease. This model used various supervised machine learning algorithms along with ensemble classifier model to analyze the COVID-19 infections in patients on the basis of the symptoms.
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Kumari, A., Mehta, A.K. (2022). Effective Prediction of COVID-19 Using Supervised Machine Learning with Ensemble Modeling. In: Dua, M., Jain, A.K., Yadav, A., Kumar, N., Siarry, P. (eds) Proceedings of the International Conference on Paradigms of Communication, Computing and Data Sciences. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-16-5747-4_45
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DOI: https://doi.org/10.1007/978-981-16-5747-4_45
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