Artificial Intelligence and Machine Learning for COVID-19
Springer International Publishing (Verlag)
978-3-030-60190-4 (ISBN)
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.
lt;b>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, in addition 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).
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.
| Erscheinungsdatum | 22.02.2022 |
|---|---|
| Reihe/Serie | Studies in Computational Intelligence |
| Zusatzinfo | X, 266 p. 105 illus., 91 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 427 g |
| Themenwelt | Technik ► Elektrotechnik / Energietechnik |
| Technik ► Nachrichtentechnik | |
| Schlagworte | Artificial Intelligence and COVID-19 • Cloud Computing and COVID-19 • COVID-19 and IoT • Internet of Things and COVID-19 • Machine Learning and COVID-19 |
| ISBN-10 | 3-030-60190-0 / 3030601900 |
| ISBN-13 | 978-3-030-60190-4 / 9783030601904 |
| Zustand | Neuware |
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