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Computational Intelligence for Managing Pandemics
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Edited by:
Language:
English
Published/Copyright:
2021
About this book
This book uncovers the stakes and possibilities of handling pandemic diseases with the help of Computational Intelligence, using cases and applications from the current Covid-19 pandemic. The book chapters will focus on the application of CI and its related fields in managing different aspects of Covid-19, including modelling of the disease spread, data-driven prediction, identification of disease hotspots, and medical decision support.
Author / Editor information
A. Khamparia, LPU, India; B. Bhushan, HMRITM, India; M.R.H. Mondal, P. Podder, BUET, Bangladesh; V.H. de Albuquerque, UNIFOR, Brazil.
Topics
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Frontmatter
I -
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Preface
V -
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Contents
XIII -
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About the editors
XV -
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List of contributors
XVII -
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1 Application of rough set theory to analyze primary parameters causing death in COVID-19 patients
1 -
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2 From Wuhan to Africa: insights into the genome of the SARS-CoV-2
17 -
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3 Analysis of divergence aspects of breast in breast cancer patients that change due to COVID-19
31 -
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4 The correlates among containment, management and public interest indicators of COVID-19 in Nigeria: managerial and policy implications for stakeholders
57 -
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5 Effect of lockdown during the COVID-19 pandemic using mathematical modeling: a quantitative saatudy
75 -
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6 Flattening the curve of COVID-19 outbreak by early forecasting
95 -
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7 Analysis and forecasting of COVID-19 infections in India using ARIMA model
121 -
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8 Effectiveness of machine learning in predicting the spread of COVID-19
131 -
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9 Mathematical modeling of the transmission dynamics of novel coronavirus: an India-specific study
151 -
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10 The role of IoMT during pandemics
169 -
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11 Internet of medical things approach to COVID-19
187 -
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12 Applications and challenges of AI-driven IoHT for combating pandemics: a review
213 -
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13 Deep learning on medical images to combat a pandemic
231 -
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14 Deep convolutional neural network for the classification of COVID-19 from chest X-ray images
259 -
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15 Deep learning for analysis of COVID-19 electronic health records
293 -
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Index
319
Publishing information
Pages and Images/Illustrations in book
eBook published on:
September 7, 2021
eBook ISBN:
9783110712254
Hardcover published on:
September 7, 2021
Hardcover ISBN:
9783110700206
Pages and Images/Illustrations in book
Front matter:
19
Main content:
321
Illustrations:
29
Coloured Illustrations:
47
Tables:
20
Audience(s) for this book
Researchers, Graduates, Professionals, Institutions.
Safety & product resources
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Manufacturer information:
Walter de Gruyter GmbH
Genthiner Straße 13
10785 Berlin
productsafety@degruyterbrill.com
