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Post COVID-19 Intelligent Public Healthcare Management
2021 IEEE Globecom Workshops, GC Wkshps 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1746093
ABSTRACT
Epidemic outbreaks are collective effects of ongoing globalization, urbanisation, population mobility, climate change, demographic change and evolution of newer strains of infectious agents that result in high morbidity, mortality and huge financial loss, such as COVID-19. Thus, the early prediction of the emergence of a disease can play a pivotal role to prevent a disease to become epidemic. The Edge AI based solution has been proposed for healthcare prediction using machine learning (ML). In this paper, our focus is to propose ML based advanced model for public healthcare to reduce and control epidemic outbreaks. Collective knowledge from interconnected disciplines, shared data repository, and diverse roles have been embedded into the proposed framework. An evaluation based on actual COVID-19 related data demonstrates that ML can be used for COVID risk prediction for public health data as well as to take preventive steps to combat epidemics in early-stage. © 2021 IEEE.
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Full text: Available Collection: Databases of international organizations Database: Scopus Topics: Long Covid Language: English Journal: 2021 IEEE Globecom Workshops, GC Wkshps 2021 Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Topics: Long Covid Language: English Journal: 2021 IEEE Globecom Workshops, GC Wkshps 2021 Year: 2021 Document Type: Article