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Computational Intelligence Methods in COVID-19: Surveillance, Prevention, Prediction and Diagnosis

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Cover of 'Computational Intelligence Methods in COVID-19: Surveillance, Prevention, Prediction and Diagnosis'

Table of Contents

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    Book Overview
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    Chapter 1 An Introduction to Computational Intelligence in COVID-19: Surveillance, Prevention, Prediction, and Diagnosis
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    Chapter 2 Role of Computational Intelligence Against COVID-19
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    Chapter 3 Using Computational Intelligence for Tracking COVID-19 Outbreak in Online Social Networks
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    Chapter 4 Social Network Analysis for the Identification of Key Spreaders During COVID-19
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    Chapter 5 Mobile Technology Solution for COVID-19: Surveillance and Prevention
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    Chapter 6 The Role of Internet of Things (IoT) in the Containment and Spread of the Novel COVID-19 Pandemic
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    Chapter 7 A Review on Predictive Systems and Data Models for COVID-19
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    Chapter 8 A Comparative Study of the SIR Prediction Models and Disease Control Strategies: A Case Study of the State of Kerala, India
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    Chapter 9 Computational Intelligence Approach for Prediction of COVID-19 Using Particle Swarm Optimization
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    Chapter 10 COVID-19 Insightful Data Visualization and Forecasting Using Elasticsearch
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    Chapter 11 Computational Intelligence Methods for the Diagnosis of COVID-19
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    Chapter 12 Rapid Computer Diagnosis for the Deadly Zoonotic COVID-19 Infection
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    Chapter 13 Computational Intelligence Methods in Medical Image-Based Diagnosis of COVID-19 Infections
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    Chapter 14 Computational Intelligence in Drug Repurposing for COVID-19
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    Chapter 15 COVID-19: Hard Road to Find Integrated Computational Drug and Repurposing Pipeline
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    Chapter 16 Computational Intelligence in Vaccine Design Against COVID-19
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    Chapter 17 Big Data Analytics for Understanding and Fighting COVID-19
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    Chapter 18 IoMT Potential Impact in COVID-19: Combating a Pandemic with Innovation
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    Chapter 19 Advances in Intelligent Based Internet of Medical Things (IoMT) for COVID-19: Olfactory Disorders
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    Chapter 20 Integrating M-Health with IoMT to Counter COVID-19
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    Chapter 21 Digital Image Analysis Is a Silver Bullet to COVID-19 Pandemic
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    Chapter 22 Non Linear Tensor Diffusion Based Unsharp Masking for Filtering of COVID-19 CT Images
Attention for Chapter 4: Social Network Analysis for the Identification of Key Spreaders During COVID-19
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Citations

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Chapter title
Social Network Analysis for the Identification of Key Spreaders During COVID-19
Chapter number 4
Book title
Computational Intelligence Methods in COVID-19: Surveillance, Prevention, Prediction and Diagnosis
Published by
Springer, Singapore, October 2020
DOI 10.1007/978-981-15-8534-0_4
Book ISBNs
978-9-81-158533-3, 978-9-81-158534-0
Authors

Ahmadi Hasan, Ahmad Kamal, Hasan, Ahmadi, Kamal, Ahmad

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Other 2 22%
Student > Master 2 22%
Researcher 2 22%
Student > Bachelor 1 11%
Unspecified 1 11%
Other 1 11%
Readers by discipline Count As %
Medicine and Dentistry 2 22%
Arts and Humanities 1 11%
Unspecified 1 11%
Philosophy 1 11%
Mathematics 1 11%
Other 3 33%