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  Published Paper Details:

  Paper Title

MULTI FEATURE EXTRACTION BASED AND EUCLIDEAN SIMILARITY BASED SEVERITY PREDICTION OF COVID-19

  Authors

  Shraddha R. Satpute,  Prof.Rahul.L.Paikrao

  Keywords

Pandemic, Artificial Intelligence, Machine Learning

  Abstract


As we all know that Corona Virus is rise of COVID-19 pandemic communicable disease. it absoluately was first identified in Wuhan in December 2019. It expanded its circle everywhere the globe and eventually spreading its route to India. the full world is fighting against the spread of this deadly disease, cases in India also gradually increasing day by day since May after lockdown. This paper proposes a way to contribute to utilizing the machine learning and deep learning models with the aim for understanding its everyday exponential behavior together with the prediction of future reachability of the COVID-2019 across the nations by utilizing the real-time information from the Johns Hopkins. This paper studies the COVID-19 dataset and explore the information by data visualization with different libraries that are available in Python. The paper also discusses this situation in India while tackling the Covid-19 pandemic and also the ongoing development in AI and ML has significantly improved treatment, medication, screening tests, prediction, forecasting, contact tracing, and drug/vaccine development process for the Covid19 pandemic and reduce the human intervention in practice.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2205330

  Paper ID - 219440

  Page Number(s) - c900-c904

  Pubished in - Volume 10 | Issue 5 | May 2022

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Shraddha R. Satpute,  Prof.Rahul.L.Paikrao,   "MULTI FEATURE EXTRACTION BASED AND EUCLIDEAN SIMILARITY BASED SEVERITY PREDICTION OF COVID-19", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.10, Issue 5, pp.c900-c904, May 2022, Available at :http://www.ijcrt.org/papers/IJCRT2205330.pdf

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ISSN: 2320-2882
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ISSN and 7.97 Impact Factor Details


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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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