Staff View: Computational Intelligence for Managing Pandemics /

Computational Intelligence for Managing Pandemics / / ed. by Aditya Khamparia, Rubaiyat Hossain Mondal, Prajoy Podder, Bharat Bhushan, Victor Hugo C. de Albuquerque, Sachin Kumar.

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 Co...

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Superior document:	Title is part of eBook package: De Gruyter DG Ebook Package English 2021
MitwirkendeR:	Ajetunmobi, Umar Olansile, Asif, Sohaib, Bandyopadhyay, Samir Kumar, Bharati, Subrato, Bhushan, Bharat, Chauhan, Sunita S., Dargad, Sweta A., Dixit, Sunanda, Dutta, Shawni, Gbolagade Adiamoh, Abdul Ganiyy, Hossain Mondal, M. Rubaiyat, Hou, Jin, Joshi, Nisheeth, Katyayan, Pragya, Kébé, Khadim, Lasisi, Mutiu Iyanda, Mahalakshmi, J., Mahesh, Riya, Mehendale, Ninad, Pachpatte, Deepak, Pandey, Anupriya, Patel, Rutwik, Paul, Pinto Kumar, Podder, Prajoy, Sharma, Leena, Sharma, Utkarsh, Sharmy, Nure Naushin, Si, Jinhai, Uppal, Arushi, Yi, Tao, Yi, Wenhui,
HerausgeberIn:	Albuquerque, Victor Hugo C. de, Bhushan, Bharat, Hossain Mondal, Rubaiyat, Khamparia, Aditya, Kumar, Sachin, Podder, Prajoy,
Place / Publishing House:	Berlin ;, Boston : : De Gruyter, , [2021] ©2021
Year of Publication:	2021
Language:	English
Series:	Intelligent Biomedical Data Analysis , 5
Online Access:	https://doi.org/10.1515/9783110712254 https://www.degruyter.com/isbn/9783110712254 Cover
Physical Description:	1 online resource (XIX, 321 p.)
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id	9783110712254
ctrlnum	(DE-B1597)563382 (OCoLC)1266229255
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spelling	Computational Intelligence for Managing Pandemics / ed. by Aditya Khamparia, Rubaiyat Hossain Mondal, Prajoy Podder, Bharat Bhushan, Victor Hugo C. de Albuquerque, Sachin Kumar. Berlin ; Boston : De Gruyter, [2021] ©2021 1 online resource (XIX, 321 p.) text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Intelligent Biomedical Data Analysis , 2629-7140 ; 5 Frontmatter -- Preface -- Contents -- About the editors -- List of contributors -- 1 Application of rough set theory to analyze primary parameters causing death in COVID-19 patients -- 2 From Wuhan to Africa: insights into the genome of the SARS-CoV-2 -- 3 Analysis of divergence aspects of breast in breast cancer patients that change due to COVID-19 -- 4 The correlates among containment, management and public interest indicators of COVID-19 in Nigeria: managerial and policy implications for stakeholders -- 5 Effect of lockdown during the COVID-19 pandemic using mathematical modeling: a quantitative saatudy -- 6 Flattening the curve of COVID-19 outbreak by early forecasting -- 7 Analysis and forecasting of COVID-19 infections in India using ARIMA model -- 8 Effectiveness of machine learning in predicting the spread of COVID-19 -- 9 Mathematical modeling of the transmission dynamics of novel coronavirus: an India-specific study -- 10 The role of IoMT during pandemics -- 11 Internet of medical things approach to COVID-19 -- 12 Applications and challenges of AI-driven IoHT for combating pandemics: a review -- 13 Deep learning on medical images to combat a pandemic -- 14 Deep convolutional neural network for the classification of COVID-19 from chest X-ray images -- 15 Deep learning for analysis of COVID-19 electronic health records -- Index restricted access http://purl.org/coar/access_right/c_16ec online access with authorization star 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. Issued also in print. Mode of access: Internet via World Wide Web. In English. Description based on online resource; title from PDF title page (publisher's Web site, viewed 28. Feb 2023) Big data. Computational intelligence. Epidemics Data processing. Public health Data processing. Algorithmus. Big Data. Digital Health. Öffentliche Gesundheit. COMPUTERS / Intelligence (AI) & Semantics. bisacsh Ajetunmobi, Umar Olansile, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Albuquerque, Victor Hugo C. de, editor. edt http://id.loc.gov/vocabulary/relators/edt Asif, Sohaib, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Bandyopadhyay, Samir Kumar, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Bharati, Subrato, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Bhushan, Bharat, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Bhushan, Bharat, editor. edt http://id.loc.gov/vocabulary/relators/edt Chauhan, Sunita S., contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Dargad, Sweta A., contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Dixit, Sunanda, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Dutta, Shawni, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Gbolagade Adiamoh, Abdul Ganiyy, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Hossain Mondal, M. Rubaiyat, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Hossain Mondal, Rubaiyat, editor. edt http://id.loc.gov/vocabulary/relators/edt Hou, Jin, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Joshi, Nisheeth, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Katyayan, Pragya, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Khamparia, Aditya, editor. edt http://id.loc.gov/vocabulary/relators/edt Kumar, Sachin, editor. edt http://id.loc.gov/vocabulary/relators/edt Kébé, Khadim, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Lasisi, Mutiu Iyanda, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Mahalakshmi, J., contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Mahesh, Riya, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Mehendale, Ninad, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Pachpatte, Deepak, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Pandey, Anupriya, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Patel, Rutwik, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Paul, Pinto Kumar, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Podder, Prajoy, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Podder, Prajoy, editor. edt http://id.loc.gov/vocabulary/relators/edt Sharma, Leena, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Sharma, Utkarsh, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Sharmy, Nure Naushin, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Si, Jinhai, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Uppal, Arushi, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Yi, Tao, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Yi, Wenhui, contributor. ctb https://id.loc.gov/vocabulary/relators/ctb Title is part of eBook package: De Gruyter DG Ebook Package English 2021 9783110750720 Title is part of eBook package: De Gruyter DG Plus DeG Package 2021 Part 1 9783110750706 Title is part of eBook package: De Gruyter EBOOK PACKAGE COMPLETE 2021 English 9783110754001 Title is part of eBook package: De Gruyter EBOOK PACKAGE COMPLETE 2021 9783110753776 ZDB-23-DGG Title is part of eBook package: De Gruyter EBOOK PACKAGE Engineering, Computer Sciences 2021 English 9783110754070 Title is part of eBook package: De Gruyter EBOOK PACKAGE Engineering, Computer Sciences 2021 9783110753837 ZDB-23-DEI EPUB 9783110712278 print 9783110700206 https://doi.org/10.1515/9783110712254 https://www.degruyter.com/isbn/9783110712254 Cover https://www.degruyter.com/document/cover/isbn/9783110712254/original
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author_sort	Ajetunmobi, Umar Olansile,
title	Computational Intelligence for Managing Pandemics /
spellingShingle	Computational Intelligence for Managing Pandemics / Intelligent Biomedical Data Analysis , Frontmatter -- Preface -- Contents -- About the editors -- List of contributors -- 1 Application of rough set theory to analyze primary parameters causing death in COVID-19 patients -- 2 From Wuhan to Africa: insights into the genome of the SARS-CoV-2 -- 3 Analysis of divergence aspects of breast in breast cancer patients that change due to COVID-19 -- 4 The correlates among containment, management and public interest indicators of COVID-19 in Nigeria: managerial and policy implications for stakeholders -- 5 Effect of lockdown during the COVID-19 pandemic using mathematical modeling: a quantitative saatudy -- 6 Flattening the curve of COVID-19 outbreak by early forecasting -- 7 Analysis and forecasting of COVID-19 infections in India using ARIMA model -- 8 Effectiveness of machine learning in predicting the spread of COVID-19 -- 9 Mathematical modeling of the transmission dynamics of novel coronavirus: an India-specific study -- 10 The role of IoMT during pandemics -- 11 Internet of medical things approach to COVID-19 -- 12 Applications and challenges of AI-driven IoHT for combating pandemics: a review -- 13 Deep learning on medical images to combat a pandemic -- 14 Deep convolutional neural network for the classification of COVID-19 from chest X-ray images -- 15 Deep learning for analysis of COVID-19 electronic health records -- Index
title_full	Computational Intelligence for Managing Pandemics / ed. by Aditya Khamparia, Rubaiyat Hossain Mondal, Prajoy Podder, Bharat Bhushan, Victor Hugo C. de Albuquerque, Sachin Kumar.
title_fullStr	Computational Intelligence for Managing Pandemics / ed. by Aditya Khamparia, Rubaiyat Hossain Mondal, Prajoy Podder, Bharat Bhushan, Victor Hugo C. de Albuquerque, Sachin Kumar.
title_full_unstemmed	Computational Intelligence for Managing Pandemics / ed. by Aditya Khamparia, Rubaiyat Hossain Mondal, Prajoy Podder, Bharat Bhushan, Victor Hugo C. de Albuquerque, Sachin Kumar.
title_auth	Computational Intelligence for Managing Pandemics /
title_alt	Frontmatter -- Preface -- Contents -- About the editors -- List of contributors -- 1 Application of rough set theory to analyze primary parameters causing death in COVID-19 patients -- 2 From Wuhan to Africa: insights into the genome of the SARS-CoV-2 -- 3 Analysis of divergence aspects of breast in breast cancer patients that change due to COVID-19 -- 4 The correlates among containment, management and public interest indicators of COVID-19 in Nigeria: managerial and policy implications for stakeholders -- 5 Effect of lockdown during the COVID-19 pandemic using mathematical modeling: a quantitative saatudy -- 6 Flattening the curve of COVID-19 outbreak by early forecasting -- 7 Analysis and forecasting of COVID-19 infections in India using ARIMA model -- 8 Effectiveness of machine learning in predicting the spread of COVID-19 -- 9 Mathematical modeling of the transmission dynamics of novel coronavirus: an India-specific study -- 10 The role of IoMT during pandemics -- 11 Internet of medical things approach to COVID-19 -- 12 Applications and challenges of AI-driven IoHT for combating pandemics: a review -- 13 Deep learning on medical images to combat a pandemic -- 14 Deep convolutional neural network for the classification of COVID-19 from chest X-ray images -- 15 Deep learning for analysis of COVID-19 electronic health records -- Index
title_new	Computational Intelligence for Managing Pandemics /
title_sort	computational intelligence for managing pandemics /
series	Intelligent Biomedical Data Analysis ,
series2	Intelligent Biomedical Data Analysis ,
publisher	De Gruyter,
publishDate	2021
physical	1 online resource (XIX, 321 p.) Issued also in print.
contents	Frontmatter -- Preface -- Contents -- About the editors -- List of contributors -- 1 Application of rough set theory to analyze primary parameters causing death in COVID-19 patients -- 2 From Wuhan to Africa: insights into the genome of the SARS-CoV-2 -- 3 Analysis of divergence aspects of breast in breast cancer patients that change due to COVID-19 -- 4 The correlates among containment, management and public interest indicators of COVID-19 in Nigeria: managerial and policy implications for stakeholders -- 5 Effect of lockdown during the COVID-19 pandemic using mathematical modeling: a quantitative saatudy -- 6 Flattening the curve of COVID-19 outbreak by early forecasting -- 7 Analysis and forecasting of COVID-19 infections in India using ARIMA model -- 8 Effectiveness of machine learning in predicting the spread of COVID-19 -- 9 Mathematical modeling of the transmission dynamics of novel coronavirus: an India-specific study -- 10 The role of IoMT during pandemics -- 11 Internet of medical things approach to COVID-19 -- 12 Applications and challenges of AI-driven IoHT for combating pandemics: a review -- 13 Deep learning on medical images to combat a pandemic -- 14 Deep convolutional neural network for the classification of COVID-19 from chest X-ray images -- 15 Deep learning for analysis of COVID-19 electronic health records -- Index
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issn	2629-7140 ;
callnumber-first	Q - Science
callnumber-subject	Q - General Science
callnumber-label	Q342
callnumber-sort	Q 3342 C66 42021
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illustrated	Not Illustrated
dewey-hundreds	000 - Computer science, information & general works
dewey-tens	000 - Computer science, knowledge & systems
dewey-ones	004 - Data processing & computer science
dewey-full	004
dewey-sort	14
dewey-raw	004
dewey-search	004
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oclc_num	1266229255
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file</subfield><subfield code="b">PDF</subfield><subfield code="2">rda</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Intelligent Biomedical Data Analysis ,</subfield><subfield code="x">2629-7140 ;</subfield><subfield code="v">5</subfield></datafield><datafield tag="505" ind1="0" ind2="0"><subfield code="t">Frontmatter -- </subfield><subfield code="t">Preface -- </subfield><subfield code="t">Contents -- </subfield><subfield code="t">About the editors -- </subfield><subfield code="t">List of contributors -- </subfield><subfield code="t">1 Application of rough set theory to analyze primary parameters causing death in COVID-19 patients -- </subfield><subfield code="t">2 From Wuhan to Africa: insights into the genome of the SARS-CoV-2 -- </subfield><subfield code="t">3 Analysis of divergence aspects of breast in breast cancer patients that change due to COVID-19 -- </subfield><subfield code="t">4 The correlates among containment, management and public interest indicators of COVID-19 in Nigeria: managerial and policy implications for stakeholders -- </subfield><subfield code="t">5 Effect of lockdown during the COVID-19 pandemic using mathematical modeling: a quantitative saatudy -- </subfield><subfield code="t">6 Flattening the curve of COVID-19 outbreak by early forecasting -- </subfield><subfield code="t">7 Analysis and forecasting of COVID-19 infections in India using ARIMA model -- </subfield><subfield code="t">8 Effectiveness of machine learning in predicting the spread of COVID-19 -- </subfield><subfield code="t">9 Mathematical modeling of the transmission dynamics of novel coronavirus: an India-specific study -- </subfield><subfield code="t">10 The role of IoMT during pandemics -- </subfield><subfield code="t">11 Internet of medical things approach to COVID-19 -- </subfield><subfield code="t">12 Applications and challenges of AI-driven IoHT for combating pandemics: a review -- </subfield><subfield code="t">13 Deep learning on medical images to combat a pandemic -- </subfield><subfield code="t">14 Deep convolutional neural network for the classification of COVID-19 from chest X-ray images -- </subfield><subfield code="t">15 Deep learning for analysis of COVID-19 electronic health records -- </subfield><subfield code="t">Index</subfield></datafield><datafield tag="506" ind1="0" ind2=" "><subfield code="a">restricted access</subfield><subfield code="u">http://purl.org/coar/access_right/c_16ec</subfield><subfield code="f">online access with authorization</subfield><subfield code="2">star</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">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.</subfield></datafield><datafield tag="530" ind1=" " ind2=" "><subfield code="a">Issued also in print.</subfield></datafield><datafield tag="538" ind1=" " ind2=" "><subfield code="a">Mode of access: Internet via World Wide Web.</subfield></datafield><datafield tag="546" ind1=" " ind2=" "><subfield code="a">In English.</subfield></datafield><datafield tag="588" ind1="0" ind2=" "><subfield code="a">Description based on online resource; title from PDF title page (publisher's Web site, viewed 28. Feb 2023)</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Big data.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Computational intelligence.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Epidemics</subfield><subfield code="x">Data processing.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Public health</subfield><subfield code="x">Data processing.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Algorithmus.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Big Data.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Digital Health.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Öffentliche Gesundheit.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">COMPUTERS / Intelligence (AI) & Semantics.</subfield><subfield code="2">bisacsh</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ajetunmobi, Umar Olansile, </subfield><subfield code="e">contributor.</subfield><subfield code="4">ctb</subfield><subfield code="4">https://id.loc.gov/vocabulary/relators/ctb</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Albuquerque, Victor Hugo C. de, </subfield><subfield code="e">editor.</subfield><subfield code="4">edt</subfield><subfield code="4">http://id.loc.gov/vocabulary/relators/edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Asif, Sohaib, </subfield><subfield code="e">contributor.</subfield><subfield code="4">ctb</subfield><subfield code="4">https://id.loc.gov/vocabulary/relators/ctb</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Bandyopadhyay, Samir Kumar, </subfield><subfield code="e">contributor.</subfield><subfield code="4">ctb</subfield><subfield code="4">https://id.loc.gov/vocabulary/relators/ctb</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Bharati, Subrato, </subfield><subfield code="e">contributor.</subfield><subfield code="4">ctb</subfield><subfield code="4">https://id.loc.gov/vocabulary/relators/ctb</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Bhushan, Bharat, </subfield><subfield code="e">contributor.</subfield><subfield code="4">ctb</subfield><subfield code="4">https://id.loc.gov/vocabulary/relators/ctb</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Bhushan, Bharat, </subfield><subfield code="e">editor.</subfield><subfield code="4">edt</subfield><subfield code="4">http://id.loc.gov/vocabulary/relators/edt</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Chauhan, Sunita S., </subfield><subfield code="e">contributor.</subfield><subfield code="4">ctb</subfield><subfield code="4">https://id.loc.gov/vocabulary/relators/ctb</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Dargad, Sweta A., </subfield><subfield code="e">contributor.</subfield><subfield code="4">ctb</subfield><subfield code="4">https://id.loc.gov/vocabulary/relators/ctb</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Dixit, Sunanda, </subfield><subfield code="e">contributor.</subfield><subfield code="4">ctb</subfield><subfield code="4">https://id.loc.gov/vocabulary/relators/ctb</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Dutta, Shawni, </subfield><subfield code="e">contributor.</subfield><subfield code="4">ctb</subfield><subfield code="4">https://id.loc.gov/vocabulary/relators/ctb</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Gbolagade Adiamoh, Abdul Ganiyy, </subfield><subfield code="e">contributor.</subfield><subfield code="4">ctb</subfield><subfield code="4">https://id.loc.gov/vocabulary/relators/ctb</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Hossain Mondal, M. 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Computational Intelligence for Managing Pandemics / / ed. by Aditya Khamparia, Rubaiyat Hossain Mondal, Prajoy Podder, Bharat Bhushan, Victor Hugo C. de Albuquerque, Sachin Kumar.

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