Data Science for COVID-19 Volume 1: Computational Perspectives

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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.

• 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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