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Big Data Analytics and Artificial Intelligence Against COVID-19: Innovation Vision and Approach / edited by Aboul-Ella Hassanien, Nilanjan Dey, Sally Elghamrawy.

SpringerLink Books Computer Science (2011-2024) Available online

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Format:
Book
Contributor:
Hassanien, Aboul Ella, editor.
Dey, Nilanjan, 1984- editor.
Elghamrawy, Sally, editor.
SpringerLink (Online service)
Series:
Computer Science (SpringerNature-11645)
Studies in big data 2197-6503 ; 78.
Studies in Big Data, 2197-6503 ; 78
Language:
English
Subjects (All):
Engineering--Data processing.
Engineering.
Artificial intelligence.
Computational intelligence.
Biomedical engineering.
Epidemiology.
Big data.
Data Engineering.
Artificial Intelligence.
Computational Intelligence.
Biomedical Engineering and Bioengineering.
Big Data.
Local Subjects:
Data Engineering.
Artificial Intelligence.
Computational Intelligence.
Biomedical Engineering and Bioengineering.
Epidemiology.
Big Data.
Physical Description:
1 online resource (XI, 307 pages) : 169 illustrations, 130 illustrations in color.
Edition:
First edition 2020.
Contained In:
Springer Nature eBook
Place of Publication:
Cham : Springer International Publishing : Imprint: Springer, 2020.
System Details:
text file PDF
Summary:
This book includes research articles and expository papers on the applications of artificial intelligence and big data analytics to battle the pandemic. In the context of COVID-19, this book focuses on how big data analytic and artificial intelligence help fight COVID-19. The book is divided into four parts. The first part discusses the forecasting and visualization of the COVID-19 data. The second part describes applications of artificial intelligence in the COVID-19 diagnosis of chest X-Ray imaging. The third part discusses the insights of artificial intelligence to stop spread of COVID-19, while the last part presents deep learning and big data analytics which help fight the COVID-19. .
Contents:
Coronavirus Spreading Forecasts based on Susceptible-Infectious- Recovered and Linear Regression Model
Virus Graph and COVID-19 Pandemic: A Graph Theory Approach
Nonparametric Analysis of Tracking Data in the Context of COVID-19 Pandemic
Visualization and prediction of trends of Covid-19 pandemic during early outbreak in India using DNN and SVR
The Detection of COVID-19 in CT Medical Images: A Deep Learning Approach
COVID-19 Data Analysis and Innovative approach in Prediction of Cases
Detection of COVID-19 using Chest Radiographs with Intelligent Deployment Architecture
COVID-19 Diagnostics from the Chest X-Ray Image Using Corner-Based Weber Local Descriptor
Why are Generative Adversarial Networks Vital for Deep Neural Networks? A Case Study on COVID-19 Chest X-Ray Images
Artificial intelligence against COVID-19: A meta-analysis of current research
Insights of Artificial Intelligence to Stop Spread of COVID-19
AI based Covid19 analysis-A pragmatic approach
Artificial Intelligence and Psychosocial Support during the COVID-19 Outbreak
Role of The Accurate Detection of Core Body Temperature in The Early Detection of Coronavirus
The effect Coronavirus Pendamic on Education into Electronic Multi-Modal Smart Education
An H2O's Deep Learning-inspired model based on Big Data analytics for Coronavirus Disease (COVID-19) Diagnosis
Coronavirus (COVID-19) Classification using Deep Features Fusion and Ranking Technique
Stacking Deep Learning for Early COVID-19 Vision Diagnosis.
Other Format:
Printed edition:
ISBN:
978-3-030-55258-9
9783030552589
Access Restriction:
Restricted for use by site license.

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