Abstract
During the recent COVID-19 outbreak, all health professionals, scientists and other experts around the world started seeking for latest, effective and reliable source of technology to help track and tackle this situation surrounding the pandemic. Machine Learning, Deep Learning and Artificial Intelligence make a huge difference over traditional surveys and analysis. To come up with the well-being of living society, we prefer to utilize ML and deep learning models with the focus on understanding their everyday exponential behaviour in addition to the prediction graphs of further growth of COVID-2019 over the world by utilizing the available facts and dataset.
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References
Barstugan M, Ozkaya U, Ozturk S (2020) Coronavirus (covid-19) classification using ct images by machine learning methods. arXiv preprint arXiv:2003.09424
Basic Definitions for Outbreak Epidemic and Pandemic (n.d.). https://www.webmd.com/cold-and-flu/what-are-epidemics-pandemics-outbreaks
Covid-2019 Datasets (n.d.). https://www.kaggle.com/allen-institute-for-ai/CORD-19-research-challenge
Deep Learning Information (n.d.). https://www.tutorialspoint.com/tensorflow/tensorflow_machine_learning_deep_learning.htm
GitHub Repository (2019) 2019 Novel coronavirus COVID-19 (2019-nCoV) data repository by Johns Hopkins CSSE. https://github.com/CSSEGISandData/COVID-19. Accessed 31 Mar 2020
Machine Learning Information (n.d.). https://en.wikipedia.org/wiki/Machine_learning
Navares R, DÃaz J, Linares C, Aznarte JL (2018) Comparing ARIMA and computational intelligence methods to forecast daily hospital admissions due to circulatory and respiratory causes in Madrid. Stoch Env Res Risk Assess 32(10):2849–2859
Types of Machine Learning (n.d.). https://searchenterpriseai.techtarget.com/definition/machine%20learningML
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Akulwar, P.K., Gambhir, J.D. (2021). Prediction and Analysis of Outbreak of COVID-19 Pandemic Using Machine Learning. In: Nandan Mohanty, S., Saxena, S.K., Satpathy, S., Chatterjee, J.M. (eds) Applications of Artificial Intelligence in COVID-19 . Medical Virology: From Pathogenesis to Disease Control. Springer, Singapore. https://doi.org/10.1007/978-981-15-7317-0_14
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DOI: https://doi.org/10.1007/978-981-15-7317-0_14
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