Data Science for COVID-19, Vol. 1: Computational Perspectives

Data Science for COVID-19, Vol. 1: Computational Perspectives

Author
Utku Kose (editor), Deepak Gupta (editor), Victor Hugo Costa de Albuquerque (editor), Ashish Khanna (editor)
Publisher
Academic Press
Language
English
Year
2021
Page
752
ISBN
0128245360,9780128245361
File Type
pdf
File Size
16.4 MiB

Data Science for COVID-19 presents leading-edge research on data science techniques for the detection, mitigation, treatment and elimination of COVID-19. Sections provide an introduction to data science for COVID-19 research, considering past and future pandemics, as well as related Coronavirus variations. Other chapters cover a wide range of Data Science applications concerning COVID-19 research, including Image Analysis and Data Processing, Geoprocessing and tracking, Predictive Systems, Design Cognition, mobile technology, and telemedicine solutions. The book then covers Artificial Intelligence-based solutions, innovative treatment methods, and public safety. Finally, readers will learn about applications of Big Data and new data models for mitigation. Provides a leading-edge survey of Data Science techniques and methods for research, mitigation and 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 both positive and negative research findings Provides insights into innovative data-oriented modeling and predictive techniques from COVID-19 researchers Includes real-world feedback and user experiences from physicians and medical staff from around the world on the effectiveness of applied Data Science solutions

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