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Rapid Forecasting of Pandemic Outbreak Using Machine Learning
Enabling Healthcare 4.0 for Pandemics: A Roadmap Using AI, Machine Learning, IoT and Cognitive Technologies ; : 59-73, 2021.
Article in English | Scopus | ID: covidwho-1919208
ABSTRACT
Humans have faced a number of pandemics since the dawn of civilization, but today what we are facing is an invisible enemy novel COVID-19, causing the pandemic globally at an alarming rate, bringing a devastating effect on our lives and impacting our economy drastically. The infection in humans by COVID-19 was thought to be originally from bats perhaps as zoonotic agent (from animal to human) but the rapid increase in the figure of cases in Wuhan city and globally even after shutting the market off and quarantine whole city, indicated an alternative mode of transmission from human-to-human which is rarely observed in nature. The main objective of this chapter is to predict a rapid forecasting of pandemic outbreak using machine learning approaches. The chapter is based on a preliminary estimation about the disease, spread of disease across the globe, the possible ways of treatment, and prevention in its outbreak which makes use of technologies like machine learning which may prove beneficial to save the human race from pandemics like COVID19 in the future. © 2021 Scrivener Publishing LLC.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: Enabling Healthcare 4.0 for Pandemics: A Roadmap Using AI, Machine Learning, IoT and Cognitive Technologies Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: Enabling Healthcare 4.0 for Pandemics: A Roadmap Using AI, Machine Learning, IoT and Cognitive Technologies Year: 2021 Document Type: Article