Computational Intelligence for Managing Pandemics / 
ed. by Aditya Khamparia, Rubaiyat Hossain Mondal, Prajoy Podder, Bharat Bhushan, Victor Hugo C. de Albuquerque, Sachin Kumar. 
 - 1 online resource (XIX, 321 p.) 
 - Intelligent Biomedical Data Analysis ,  5  2629-7140 ; .
<br/><br/> 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 
<br/><br/> restricted access  http://purl.org/coar/access_right/c_16ec 
<br/><br/> 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. 
<br/><br/>
<br/><br/><br/>Mode of access: Internet via World Wide Web. 
<br/><br/><br/>In English. 
<br/><br/><label>ISBN: </label>9783110712254 
<br/><br/><label>Standard No.: </label>10.1515/9783110712254  doi 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Big data.<br/>Computational intelligence.<br/>Epidemics--Data processing.<br/>Public health--Data processing.<br/>Algorithmus.<br/>Big Data.<br/>Digital Health.<br/>Öffentliche Gesundheit.<br/>COMPUTERS / Intelligence (AI) & Semantics.
<br/><br/><label>LC Class. No.: </label>Q342  / .C66 2021 
<br/><br/><label>Dewey Class. No.: </label>004