Artificial Intelligence and Machine Learning for COVID-19 (Hardcover, 1st ed. 2021)

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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Studies in Computational Intelligence, 924
Release date:	February 2021
First published:	2021
Editors:	Fadi Al-Turjman
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	266
Edition:	1st ed. 2021
ISBN-13:	978-3-03-060187-4
Categories:	Books > Computing & IT > Social & legal aspects of computing > Health & safety aspects of computing Books > Medicine > General issues > Public health & preventive medicine > General Books > Professional & Technical > Electronics & communications engineering > Communications engineering / telecommunications > General Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	3-03-060187-0
Barcode:	9783030601874

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