Computational Intelligence for Managing Pandemics

Preface\nContents\nAbout the editors\nList of contributors\n1 Application of rough set theory to analyze primary parameters causing death in COVID-19 patients\n2 From Wuhan to Africa: insights into the genome of the SARS-CoV-2\n3 Analysis of divergence aspects of breast in breast cancer patients that change due to COVID-19\n4 The correlates among containment, management and public interest indicators of COVID-19 in Nigeria: managerial and policy implications for stakeholders\n5 Effect of lockdown during the COVID-19 pandemic using mathematical modeling: a quantitative saatudy\n6 Flattening the curve of COVID-19 outbreak by early forecasting\n7 Analysis and forecasting of COVID-19 infections in India using ARIMA model\n8 Effectiveness of machine learning in predicting the spread of COVID-19\n9 Mathematical modeling of the transmission dynamics of novel coronavirus: an India-specific study\n10 The role of IoMT during pandemics\n11 Internet of medical things approach to COVID-19\n12 Applications and challenges of AI-driven IoHT for combating pandemics: a review\n13 Deep learning on medical images to combat a pandemic\n14 Deep convolutional neural network for the classification of COVID-19 from chest X-ray images\n15 Deep learning for analysis of COVID-19 electronic health records\nIndex