Data Science for COVID-19, Volume 2: Societal and Medical Perspectives presents the most current and leading-edge research into the applications of a variety of data science techniques for the detection, mitigation, treatment and elimination of the COVID-19 virus. At this point, Cognitive Data Science is the most powerful tool for researchers to fight COVID-19. Thanks to instant data-analysis and predictive techniques, including Artificial Intelligence, Machine Learning, Deep Learning, Data Mining, and computational modeling for processing large amounts of data, recognizing patterns, modeling new techniques, and improving both research and treatment outcomes is now possible. – Provides a leading-edge survey of Data Science techniques and methods for research, mitigation and the treatment of the COVID-19 virus- Integrates various Data Science techniques to provide a resource for COVID-19 researchers and clinicians around the world, including the wide variety of impacts the virus is having on societies and medical practice- Presents insights into innovative, data-oriented modeling and predictive techniques from COVID-19 researchers around the world, including geoprocessing and tracking, lab data analysis, and theoretical views on a variety of technical applications- Includes real-world feedback and user experiences from physicians and medical staff from around the world for medical treatment perspectives, public safety policies and impacts, sociological and psychological perspectives, the effects of COVID-19 in agriculture, economies, and education, and insights on future pandemics
Victor Hugo Costa de Albuquerque & Deepak Gupta
Data Science for COVID-19 [EPUB ebook]
Volume 2: Societal and Medical Perspectives
Data Science for COVID-19 [EPUB ebook]
Volume 2: Societal and Medical Perspectives
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Bahasa Inggeris ● Format EPUB ● ISBN 9780323907705 ● Penyunting Victor Hugo Costa de Albuquerque & Deepak Gupta ● Penerbit Elsevier Science ● Diterbitkan 2021 ● Muat turun 3 kali ● Mata wang EUR ● ID 8191280 ● Salin perlindungan Adobe DRM
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