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COVID-19 Outbreak Prediction and Analysis of E-Healthcare Data Using Random Forest Algorithms
International Journal of Reliable and Quality E - Healthcare ; 11(1):2013/01/01 00:00:00.000, 2022.
Article in English | ProQuest Central | ID: covidwho-2229261
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.
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Full text: Available Collection: Databases of international organizations Database: ProQuest Central Type of study: Experimental Studies / Prognostic study / Randomized controlled trials Language: English Journal: International Journal of Reliable and Quality E - Healthcare Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: ProQuest Central Type of study: Experimental Studies / Prognostic study / Randomized controlled trials Language: English Journal: International Journal of Reliable and Quality E - Healthcare Year: 2022 Document Type: Article