Academic Press Data Science for COVID-19 Volume 1: Computational Perspectives

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. Review Examines methods and applications of Data Science and how they can contribute to new research and treatments for COVID-19 From the Back Cover Data Science for COVID-19 presents the most current and leading-edge research into the applications of a variety of data science techniques to the detection, mitigation, treatment, and elimination of the COVID-19 virus around the world. 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. Data Science for COVID-19 begins with an introduction to Data Science for COVID-19 research, considering past and potential future pandemics, as well as related Coronavirus variations. Readers will then learn about a wide range of Data Science applications concerning COVID-19 research, including Image Analysis and Data Processing, Geoprocessing and tracking, Predictive Systems, Design Cognition, and mobile technology and telemedicine solutions for remote treatment of the virus. The book then proceeds to provide insights into Artificial Intelligence-based solutions, innovative treatment methods, and public safety for COVID-19. Finally, readers will learn about applications of Big Data and new data models for understanding and mitigating the virus. About the Author Dr. Utku Kose is an Associate Professor at Su¨leyman Demirel University, Turkey. He received his PhD from Selcuk University, Turkey, in the field of computer engineering. He has more than 100 publications to his credit, including articles, authored and edited books, proceedings, and reports. He is also a series editor of the 'Biomedical and Robotics Healthcare' (CRC Press). His research interests include artificial intelligence, machine ethics, artificial intelligence safety, optimization, chaos theory, distance education, e-learning, computer education, and computer science. Dr. Gupta is an eminent academician; plays versatile roles and responsibilities within lectures, research, publications, consultancy, and community service. He has 13-years of rich expertise in teaching and two years in the industry with focus on rational-practical learning. He has served as Editor-in-Chief, Guest Editor, Associate Editor in SCI and various reputed journals. He has actively been an organizing end of various reputed international conferences. He has completed Post-Doc. from Inatel, Brazil, and PhD. from Dr. APJ Abdul Kalam Technical University. He authored / edited over 43 books, and published over 144 papers in reputed journals and conferences (including 73 SCI indexed journals). He acts also as faculty resource person, session chair, reviewer, TPC member in FDPs, conferences, and journals.. Victor Hugo C. de Albuquerque [M’17, SM’19] is a collaborator Professor and senior researcher at the Graduate Program on Teleinformatics Engineering at the Federal University of Ceará, Brazil, and at the G