Titre : | Artificial intelligence for coronavirus outbreak |
Auteurs : | Simon James Fong, Auteur Nilanjan Dey, Auteur Jyotismita Chaki, Auteur |
Editeur : | Berlin, Cham... : Springer |
Année de publication : | 2020 |
Collection : | Springer briefs in applied sciences and technology, ISSN 2191-530X |
Sous collection : | Computational intelligence |
Présentation physique : | XI, 74 p.ill., tableaux, graphiques, cartes |
ISBN/ISSN/EAN : | 978-981-1559358-- |
Autre ISBN/ISSN : | 978-981-15-5936-5 |
Mots clés : |
Covid-19 -- Gestion des crises
Intelligence artificielle Médecine -- Innovations technologiques Technologie médicale -- Prévision |
Note générale : | Notes bibliogr. |
Résumé : |
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 d[...]
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. 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. 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. [...] 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). [...] Jyotismita Chaki is currently an Assistant Professor in the School of Information Technology and Engineering at Vellore Institute of Technology, Vellore, India. She has done her Ph.D. (Engineering) from Jadavpur University, Kolkata, India. Her research interests include computer vision and image processing, machine learning, pattern recognition, medical imaging, soft computing and artificial intelligence. [...] [Présentation par le site internet de l'éditeur, juin 2020] |
Note de contenu : |
1. An Introduction to COVID-19
2. AI-Enabled Technologies that Fight the Coronavirus Outbreak
2.1. Infection Risk Identification
2.2. Smart Screening for High Body Temperature
2.3. Deep Learning and Radiological Image Analysis
2.4. AI-Dr[...]
1. An Introduction to COVID-19
2. AI-Enabled Technologies that Fight the Coronavirus Outbreak 2.1. Infection Risk Identification 2.2. Smart Screening for High Body Temperature 2.3. Deep Learning and Radiological Image Analysis 2.4. AI-Driven Unmanned Technologies 3. AI-Empowered Data Analytics for Coronavirus Epidemic Monitoring and Control 3.1. AI Predicted COVID-19 Outbreak Before It Happened 3.2. AI Predicts the Fate of COVID-19 Patients 3.3. Finding the Most Accurate Predictive Analytics 3.4. Predicting the Virus Spread by SIR and SEIR Models 4. Conclusion |
Documents numériques (2)
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