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Artificial Intelligence for Coronavirus Outbreak / / by Simon James Fong, Nilanjan Dey, Jyotismita Chaki



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Autore: Fong Simon James Visualizza persona
Titolo: Artificial Intelligence for Coronavirus Outbreak / / by Simon James Fong, Nilanjan Dey, Jyotismita Chaki Visualizza cluster
Pubblicazione: Singapore : , : Springer Singapore : , : Imprint : Springer, , 2021
Edizione: 1st ed. 2021.
Descrizione fisica: 1 online resource (84 pages)
Disciplina: 610.28563
Soggetto topico: Computational intelligence
Artificial intelligence
Data structures (Computer science)
Health informatics
Computational Intelligence
Artificial Intelligence
Data Structures and Information Theory
Health Informatics
Persona (resp. second.): DeyNilanjan
ChakiJyotismita
Nota di contenuto: An Introduction to COVID-19 -- AI-enabled Technologies that Fight the Coronavirus Outbreak -- AI-empowered Data Analytics for Coronavirus Epidemic Monitoring and Control -- Conclusion.
Sommario/riassunto: 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.
Titolo autorizzato: Artificial Intelligence for Coronavirus Outbreak  Visualizza cluster
ISBN: 981-15-5936-8
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910483209303321
Lo trovi qui: Univ. Federico II
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Serie: SpringerBriefs in Computational Intelligence, . 2625-3704