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Artificial Intelligence and Machine Learning for COVID-19 / edited by Fadi Al-Turjman.

SpringerLink Books Computer Science (2011-2024) Available online

View online
Format:
Book
Contributor:
Al-Turjman, Fadi, Editor.
SpringerLink (Online service)
Series:
Computer Science (SpringerNature-11645)
Studies in computational intelligence 1860-9503 ; 924
Studies in Computational Intelligence, 1860-9503 ; 924
Language:
English
Subjects (All):
Telecommunication.
Medical informatics.
Artificial intelligence.
Medicine, Preventive.
Health promotion.
Communications Engineering, Networks.
Health Informatics.
Artificial Intelligence.
Health Promotion and Disease Prevention.
Local Subjects:
Communications Engineering, Networks.
Health Informatics.
Artificial Intelligence.
Health Promotion and Disease Prevention.
Physical Description:
1 online resource (X, 266 pages) : 105 illustrations, 91 illustrations in color.
Edition:
1st ed. 2021.
Contained In:
Springer Nature eBook
Place of Publication:
Cham : Springer International Publishing : Imprint: Springer, 2021.
System Details:
text file PDF
Summary:
This book is dedicated to addressing the major challenges in fighting COVID-19 using artificial intelligence (AI) and machine learning (ML) - from cost and complexity to availability and accuracy. The aim of this book is to focus on both the design and implementation of AI-based approaches in proposed COVID-19 solutions that are enabled and supported by sensor networks, cloud computing, and 5G and beyond. This book presents research that contributes to the application of ML techniques to the problem of computer communication-assisted diagnosis of COVID-19 and similar diseases. The authors present the latest theoretical developments, real-world applications, and future perspectives on this topic. This book brings together a broad multidisciplinary community, aiming to integrate ideas, theories, models, and techniques from across different disciplines on intelligent solutions/systems, and to inform how cognitive systems in Next Generation Networks (NGN) should be designed, developed, and evaluated while exchanging and processing critical health information. Targeted readers are from varying disciplines who are interested in implementing the smart planet/environments vision via wireless/wired enabling technologies. Includes advances related to COVID-19 diagnosis and tracking through artificial intelligence and machine learning; Enriches the fields of AI and ML with new and innovative operational ideas aimed at aiding in efforts to combat and track COVID-19; Pertains to researchers, scientists, engineers, and practitioners in the field of computing and smart cities technologies.
Contents:
Smart Technologies for COVID-19: The Strategic Approaches in Combating the Virus
A Review on COVID-19
Artificial Intelligence in the Face of the Corona Virus Pandemic
Digital Transformation and Emerging Technologies for COVID-19 Pandemic: Social, Global and Industry Perspectives
A Deep Analysis and Prediction of COVID-19 in India: Using Ensemble Regression Approach
Image Enhancement in Healthcare Applications: A Review
DEEP LEARNING APPROACH USING 3D-ImpCNN CLASSIFICATION FOR CORONAVIRUS DISEASE
Drone-based Social Distancing, Sanitisation, Inspection, Monitoring and Control Room for COVID-19
Application of AI Techniques for COVID-19 in IoT and Big-Data Era: A Survey
APPLICATION OF IoT, AI and 5G IN the FIGHT AGAINST the COVID-19 PENDAMIC
AI techniques for Resource Management during Covid-19.
Other Format:
Printed edition:
ISBN:
978-3-030-60188-1
9783030601881
Access Restriction:
Restricted for use by site license.

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