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COVID-19 Outbreak Prediction and Analysis of E-Healthcare Data Using Random Forest Algorithms

COVID-19 Outbreak Prediction and Analysis of E-Healthcare Data Using Random Forest Algorithms

Debabrata Dansana, Raghvendra Kumar, Aishik Bhattacharjee, Chandrakanta Mahanty
Copyright: © 2022 |Volume: 11 |Issue: 1 |Pages: 13
ISSN: 2160-9551|EISSN: 2160-956X|EISBN13: 9781683182573|DOI: 10.4018/IJRQEH.297075
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MLA

Dansana, Debabrata, et al. "COVID-19 Outbreak Prediction and Analysis of E-Healthcare Data Using Random Forest Algorithms." IJRQEH vol.11, no.1 2022: pp.1-13. http://doi.org/10.4018/IJRQEH.297075

APA

Dansana, D., Kumar, R., Bhattacharjee, A., & Mahanty, C. (2022). COVID-19 Outbreak Prediction and Analysis of E-Healthcare Data Using Random Forest Algorithms. International Journal of Reliable and Quality E-Healthcare (IJRQEH), 11(1), 1-13. http://doi.org/10.4018/IJRQEH.297075

Chicago

Dansana, Debabrata, et al. "COVID-19 Outbreak Prediction and Analysis of E-Healthcare Data Using Random Forest Algorithms," International Journal of Reliable and Quality E-Healthcare (IJRQEH) 11, no.1: 1-13. http://doi.org/10.4018/IJRQEH.297075

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Abstract

The forecasting model used random forest algorithm. From the outcomes, it has been found that the regression models utilize basic linkage works and are exceptionally solid for forecast of COVID-19 cases in different countries as well as India. Current shared of worldwide COVID-19 confirmed case has been predicted by taking the world population and a comparatives study has been done on COVID-19 total cases growth for top 10 worst affected countries including US and excluding US. The ratio between confirmed cases vs. fatalities of COVID-19 is predicted and in the end a special study has been done on India where we have forecasted all the age groups affected by COVID-19 then we have extended our study to forecast the active, death and recovered cases especially in India and compared the situation with other countries.