A Novel Smart City-Based Framework on Perspectives for Application of Machine Learning in Combating COVID-19.
The spread of COVID-19 worldwide continues despite multidimensional efforts to curtail its spread and provide treatment. Efforts to contain the COVID-19 pandemic have triggered partial or full lockdowns across the globe. This paper presents a novel framework that intelligently combines machine learn...
| Publicado en: | BioMed Research International pp. 1 - 16 |
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| Autores principales: | , , , , , , , , |
| Formato: | review tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
9/11/2021
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=152394011&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 152394011 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 9/11/2021 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 152394011 152394011 152394011 10.1155/2021/5546790 152394011 ppf: 1 ppct: 15 formats: fmt: @attributes: type: P tig: atl: A Novel Smart City-Based Framework on Perspectives for Application of Machine Learning in Combating COVID-19. aug: au: Ezugwu, Absalom E. Hashem, Ibrahim Abaker Targio Oyelade, Olaide N. Almutari, Mubarak Al-Garadi, Mohammed A. Abdullahi, Idris Nasir Otegbeye, Olumuyiwa Shukla, Amit K. Chiroma, Haruna affil: School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, King Edward Road, Pietermaritzburg Campus, Pietermaritzburg, KwaZulu-Natal 3201, South Africa sug: subj: COVID-19 Pandemic Prevention and Control Machine Learning Conceptual Framework Urban Areas Internet of Things Technology Algorithms Stay-at-Home Orders Artificial Intelligence Health Care Delivery ab: The spread of COVID-19 worldwide continues despite multidimensional efforts to curtail its spread and provide treatment. Efforts to contain the COVID-19 pandemic have triggered partial or full lockdowns across the globe. This paper presents a novel framework that intelligently combines machine learning models and the Internet of Things (IoT) technology specifically to combat COVID-19 in smart cities. The purpose of the study is to promote the interoperability of machine learning algorithms with IoT technology by interacting with a population and its environment to curtail the COVID-19 pandemic. Furthermore, the study also investigates and discusses some solution frameworks, which can generate, capture, store, and analyze data using machine learning algorithms. These algorithms can detect, prevent, and trace the spread of COVID-19 and provide a better understanding of the disease in smart cities. Similarly, the study outlined case studies on the application of machine learning to help fight against COVID-19 in hospitals worldwide. The framework proposed in the study is a comprehensive presentation on the major components needed to integrate the machine learning approach with other AI-based solutions. Finally, the machine learning framework presented in this study has the potential to help national healthcare systems in curtailing the COVID-19 pandemic in smart cities. In addition, the proposed framework is poised as a pointer for generating research interests that would yield outcomes capable of been integrated to form an improved framework. pubtype: Academic Journal doctype: review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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