Artificial Intelligence and Machine Learning for COVID-19

by Fadi Al-Turjman (Editor)

Overview

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.

Product Details

ISBN-13:	9783030601881
Publisher:	Springer-Verlag New York, LLC
Publication date:	02/19/2021
Series:	Studies in Computational Intelligence , #924
Sold by:	Barnes & Noble
Format:	eBook
File size:	32 MB
Note:	This product may take a few minutes to download.

About the Author

Fadi Al-Turjman received his Ph.D. in computer science from Queen’s University, Kingston, Ontario, Canada, in 2011. He is a full professor and a research center director at Near East University, Nicosia, Cyprus. Prof. Al-Turjman is a leading authority in the areas of smart/intelligent, wireless, and mobile networks’ architectures, protocols, deployments, and performance evaluation. His publication history spans over 250 publications in journals, conferences, patents, books, and book chapters, in addition to numerous keynotes and plenary talks at flagship venues. He has authored and edited more than 25 books about cognition, security, and wireless sensor networks’ deployments in smart environments, published by Taylor and Francis, Elsevier, and Springer. He has received several recognitions and best papers’ awards at top international conferences. He also received the prestigious Best Research Paper Award from Elsevier Computer Communications Journal for the period 2015-2018, inaddition to the Top Researcher Award for 2018 at Antalya Bilim University, Turkey. Prof. Al-Turjman has led a number of international symposia and workshops in flagship communication society conferences. Currently, he serves as an associate editor and the lead guest/associate editor for several well reputed journals, including the IEEE Communications Surveys and Tutorials (IF 23.7) and the Elsevier Sustainable Cities and Society (IF 5.6).

Table of 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.

Editorial Reviews

Reviewer: Steven C Rella, MS (Rocky Vista University College of Osteopathic Medicine)
Description: This is a comprehensive discussion of the ongoing research and implementation of artificial intelligence (AI), machine learning (ML), and other emerging technologies, such as cloud computing and blockchain, used to combat COVID-19. The book is divided into 11 chapters that discuss the uses of AI and ML for COVID-19 in topics including contact tracing, diagnosis, and infection prevention. Each chapter presents a compilation of pertinent research articles from various fields, including healthcare and engineering.
Purpose: The purpose to present and discuss the ongoing research, applications, and challenges in the use of AI and ML for fighting the COVID-19 pandemic. The book effectively summarizes AI and ML technologies for its audience and reviews the extensive uses of AI and ML with an emphasis on COVID-19. The use of AI and ML in healthcare is brand new, and the research on their current and potential uses against COVID-19 has now been compiled in one book. The authors meet their objectives in this unique, high-quality book.
Audience: The authors intend this book for practitioners, engineers, and researchers in the field of digital health, computing, and smart technologies. It provides enough information for physicians to determine if these technologies can be implemented in their practice. Engineers and researchers will be able to potentially develop and improve upon the technologies this book discusses. A basic understanding of AI, ML, and healthcare is required for readers to fully grasp the concepts this book discusses. The research articles in each chapter are written by experts in their respective fields. Several figures and tables provide a sufficient summary for readers with limited time and who require succinct information.
Features: This book compiles various research studies in the fields of AI and ML, discussing emerging technologies, new applications for current technology, and the development of theoretical technologies that may shape the future of healthcare. The book is well organized and presents information in a succinct and easily digestible format. The graphics, figures, and tables augment the material presented in each chapter further engage readers. The topics of AI-aided computed tomography (CT) and radiograph (X-ray) analysis, and drone-based hospital sanitization efforts are covered in great depth in the book. AI-aided CT and X-ray analysis of chest scans can help physicians confirm a diagnosis of COVID-19 with help from an algorithm that has studied other chest scans from COVID-positive patients. The authors believe this technology could be used for other applications as well, such as determining bacterial vs. viral respiratory infections based on chest scans.
Assessment: This book covers a wide array of topics and is an excellent introduction to the world of AI and ML in the healthcare setting. It cites credible, relevant articles of research and applications of state-of-the-art AI and ML technologies that will vault healthcare into the future. Each chapter discusses different emerging technologies and their applications related to COVID-19 and other health endeavors. The sentence structure in the book is unusual at times, but this does not detract from the quality of the information. The only shortcoming of the book is that COVID-19 research is ongoing, so readers should be cautious about the currency of some stated statistics as they may have become outdated.

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