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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.
- Provides a leading-edge survey of Data Science techniques and methods for research, mitigation, and treatment of the COVID-19 virus
- Integrates the 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 insight into innovative data-oriented modeling and predictive techniques from COVID-19 researchers around the world
- Includes real-world feedback and user experiences from physicians and medical staff from around the world for the effectiveness of applied Data Science solutions
Academics (scientists, researchers, MSc. PhD. students) from the fields of Computer Science and Engineering, Biomedical Engineering, Biology, Chemistry, Electronics and Communication Engineering, and Information Technology. The audience also includes interested professionals-experts from both public and private industries of medical, computer, data science, information technologies. The book may be used in Data Science, Medical, Biomedical, Artificial Intelligence, Machine Learning, Deep Learning, and even Data (i.e. Image, Signal) Processing oriented courses given at especially Health, Biology, Biomedical Engineering or similar programs of universities, institutions
- Introduction to Data Science for COVID-1
2. Image Analysis and Data Processing for COVID-19
3. Geoprocessing / Tracking for COVID-19
4. Predictive Systems for COVID-19
5. Design Cognition and Computing for COVID-19
6. Mobile Technology Solutions for COVID-19
7. Artificial Intelligence Based Solutions for COVID-19
8. Treatment for COVID-19 with Cognitive Data Science
9. Public Safety for COVID-19
10. IoHT for COVID-19
11. Big Data for COVID-19
12. New Data Models for COVID-19
- No. of pages:
- © Academic Press 2021
- 1st April 2021
- Academic Press
- Paperback ISBN:
Dr. Kose received the BSc. degree from Gazi University, Turkey (2008). He received MSc. degree from Afyon Kocatepe University, Turkey (2010) and PhD. degree from Selcuk University, Turkey (2017). Currently, he is an Associate Professor in Suleyman Demirel University, Turkey. He has more than 100 publications including articles, books, proceedings, and reports. He is also in editorial boards of scientific journals and serves as one of the editors of the Biomedical and Robotics Healthcare book series (CRC Press). His research interest includes artificial intelligence, machine ethics, artificial intelligence safety, optimization, chaos, distance education, e-learning, computer education, and computer science.
Associate Professor, Suleyman Demirel University, Turkey
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..
Assistant Professor, Maharaja Agrasen Institute of Technology, India
Dr. Albuquerque [M’17, SM’19] is a Professor and senior researcher at the University of Fortaleza, Brazil, and Data Science Director at the Superintendency for Research and Public Safety Strategy of Ceará State, Brazil. He has PhD. in Mechanical Engineering from the Federal University of Paraíba, MSc. in Teleinformatics Engineering from the Federal University of Ceará, and he graduated in Mechatronics Engineering at the Federal Center of Technological Education of Ceará. He is at the Applied Informatics of UNIFOR and leader of the Industrial Informatics, Electronics and Health Research Group. He is a specialist in IoT, machine / deep learning, pattern recognition, and robotics.
Full Professor, Graduate Program in Applied Informatics, University of Fortaleza (UNIFOR)
Dr. Khanna has received his PhD. degree from National Institute of Technology, Kurukshetra (2017). He has completed his M. Tech. (2009) and B. Tech. from GGSIPU, Delhi (2004). He has completed his PDF from Internet of Things Lab at Inatel, Brazil. He is serving the research and academics as a teacher, researcher, guide, co-guide, keynote speaker, consultant, book author and editor, convener, and project consultant. He has around 125 research papers, book chapters, 28 books. He also has published a patent. His research interest includes image processing, distributed Systems and its variants, machine learning, evolutionary computing and many more.
Assistant Professor, Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology, Guru Gobind Singh Indraprastha University, India
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