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Artificial Intelligence for Coronavirus Outbreak, 1st ed. 2021 SpringerBriefs in Computational Intelligence Series

Langue : Anglais

Auteurs :

Couverture de l’ouvrage Artificial Intelligence for Coronavirus Outbreak
This book examines how the wonders of AI have contributed to the battle against COVID-19. Just as history repeats itself, so do epidemics and pandemics. In the face of the novel coronavirus disease, COVID-19, the book explores whether, in this digital era where artificial intelligence is successfully applied in all areas of industry, we are doing any better than our ancestors did in dealing with pandemics. One of the most contagious diseases ever known, COVID-19 is spreading like wildfire around and has cost thousands of human lives.

The book discusses how AI can help fight this deadly virus, from early warnings, prompt emergency responses, and critical decision-making to surveillance drones. Serving as a technical reference resource, data analytic tutorial and a chronicle of the application of AI in epidemics, this book will appeal to academics, students, data scientists, medical practitioners, and anybody who is concerned about this global epidemic.
An Introduction to COVID-19.- AI-enabled Technologies that Fight the Coronavirus Outbreak.- AI-empowered Data Analytics for Coronavirus Epidemic Monitoring and Control.- Conclusion.
Simon Fong graduated from La Trobe University, Australia, with a 1st Class Honors B.E. Computer Systems degree and a Ph.D. Computer Science degree in 1993 and 1998, respectively. Simon is now working as an Associate Professor at the Computer and Information Science Department of the University of Macau. He is a co-founder of the Data Analytics and Collaborative Computing Research Group in the Faculty of Science and Technology. Prior to his academic career, Simon took up various managerial and technical posts, such as Systems Engineer, IT Consultant, and E-commerce Director in Australia and Asia. Dr. Fong has published over 380 international conference and peer-reviewed journal papers, mostly in the areas of data mining, data stream mining, big data analytics, meta-heuristics optimization algorithms, and their applications. He serves on the editorial boards of the Journal of Network and Computer Applications of Elsevier, IEEE IT Professional Magazine, and various special issues of SCIE-indexed journals. 

Nilanjan Dey is an Assistant Professor in the Department of Information Technology at Techno International New Town (Formerly known as Techno India College of Technology), Kolkata, India. He is a Visiting Fellow of the University of Reading, UK. He is a Visiting Professor at Duy Tan University, Vietnam. He was an honorary Visiting Scientist at Global Biomedical Technologies Inc., CA, USA (2012–2015). He was awarded his Ph.D. from Jadavpur University in 2015. He is the Editor-in-Chief of the International Journal of Ambient Computing and Intelligence, IGI Global. He is the Series Co-Editor of Springer Tracts in Nature-Inspired Computing, Springer Nature, Series Co-Editor of Advances in Ubiquitous Sensing Applications for Healthcare, Elsevier, and Series Editor of Computational Intelligence in Engineering Problem Solving and Intelligent Signal processing and data analysis, CRC. He has authored/edited more than 50 books
Discusses AI-assisted technologies in the fight against coronavirus Presents data analytics for coronavirus epidemic monitoring and control Serves as a technical reference resource and data analytic tutorial

Date de parution :

Ouvrage de 74 p.

15.5x23.5 cm

Disponible chez l'éditeur (délai d'approvisionnement : 15 jours).

63,29 €

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