Data Science for COVID-19 Volume 1: Computational Perspectives
by Utku Kose (Editor), Deepak Gupta (Editor), Victor Hugo Costa de Albuquerque (Editor), Ashish Khanna (Editor)
English | 2021 | ISBN: 0128245360 | 754 pages | PDF | 16.38 MB

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.
[list]
[*]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
[/list]

https://nitro.download скачать/view/55EF600D1857E0C/Data_Science_for_COVID-19_Volume_1.pdf

https://rapidgator.net/file/fb5f7045c446605f93b6a3b957d68723/Data_Science_for_COVID-19_Volume_1.pdf.html