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kose utku (curatore); gupta deepak (curatore); de albuquerque victor hugo costa (curatore); khanna ashish (curatore) - data science for covid-19

Data Science for COVID-19 Volume 2: Societal and Medical Perspectives

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Genere:Libro
Lingua: Inglese
Pubblicazione: 10/2021





Note Editore

Data Science for COVID-19, Volume 2: Societal and Medical Perspectives presents the most current and leading-edge research into the applications of a variety of data science techniques for the detection, mitigation, treatment and elimination of the COVID-19 virus. 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 is now possible.

  • Provides a leading-edge survey of Data Science techniques and methods for research, mitigation and the 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 the wide variety of impacts the virus is having on societies and medical practice
  • Presents insights into innovative, data-oriented modeling and predictive techniques from COVID-19 researchers around the world, including geoprocessing and tracking, lab data analysis, and theoretical views on a variety of technical applications
  • Includes real-world feedback and user experiences from physicians and medical staff from around the world for medical treatment perspectives, public safety policies and impacts, sociological and psychological perspectives, the effects of COVID-19 in agriculture, economies, and education, and insights on future pandemics




Sommario

1. Essentials of COVID-19 Coronaviruses
2. Molecular Docking Study of Transmembrane serine protease type-2 inhibitors for the treatment of covid-19
3. Gut-lung crosstalk in COVID-19 pathology and fatality rate
4. Data Sharing and Privacy Issues Arising with COVID-19 Data and Applications
5. COVID-19 Outlook in the United States of America: A Data Driven Thematic Approach
6. Artificial Intelligence and COVID-19: Fighting Pandemics
7. Data Science A Survey on Statistical Analysis of the Latest Outbreak of 2019 Pandemic Novel Corona virus Disease (COVID-19) using ANOVA
8. Application of Big Data in the COVID-19 Pandemic
9. Artificial Intelligence based Solutions for COVID-19
10. Telemedicine applications for pandemic diseases with a focus on COVID-19
11. Impact of COVID-19 and Lockdown Policies on Farming, Food Security and Agribusiness in West Africa
12. Study and Impact Analysis of COVID-19 Pandemic Clinical Data on Infection Spreading
13. Towards Analyzing the Impact of HealthCare Treatments in Industry 4.0 Environment - A self-care case study during Covid-19 Outbreak
14. Big Data Processing and Analysis on the Impact of COVID-19 on Public Transport Delay
15. The Role of Societal Research and Development Center in Analyzing Society in Pandemic Times
16. Modelling and Predicting the Spread of COVID-19: A Continental Analysis
17. Applications of BIM for Disease Spread Assessment due to the Organisation of Building Artefacts
18. COVID-19 DIAGNOSIS-MYTHS AND PROTOCOLS
19. Quarantine within Quarantine: COVID-19 and GIS Scenario Dynamics Modelling in Tasmania, Australia
20. Essentials of COVID-19 and Treatment Approaches
21. Coronavirus Epidemic and Its Social / Mental Dimensions
22. Coronavirus: A Scientometric Study of World Research Publications
23. The Effects of COVID-19 Pandemic on Western Balkan Financial Markets
24. Prioritization of health emergency research and disaster preparedness: a systematic assessment of corona virus disease 2019 (COVID-19) pandemic
25. A Review on Epidemiology, Genomic Characteristics, Spread and Treatments of COVID-19
26. Control of antibiotic resistance and super infections as a strategy to manage COVID-19 deaths
27. Assessment of global research trends in the application of data science, deep and machine learning to COVID-19 pandemic
28. Identification of lead inhibitors of TMPRSS2 isoform 1 of SARS-CoV-2 target using Neural Network, Random Forest and molecular docking
29. The linkage between epidemic of COVID-19 and oil prices: Case of Saudi Arabia, January 22 - April 17
30. Role of Big Geospatial Data in the COVID-19 Crisis
31. COVID-19: Will it be a Game Changer in Higher Education in India?
32. Are Northern and Southern Regions equally affected by the COVID-19 Pandemic? Empirical Evidence from Nigeria
33. Covid-19 lethality reduction using Artificial Intelligence Solutions derived from Telecommunications Systems
34. The significance of Daily Increase and Mortality Cases due to COVID-19 in some African Countries
35. Data Interpretation Leading to Image Processing: A Hybrid Perspective to A Global Pandemic- COVID19
36. COVID-19: Monitoring the pandemic in India
37. Potential Antiviral Therapies for Corona Virus Disease (COVID-19)




Autore

Dr. Utku Kose is an Associate Professor at Süleyman Demirel University, Turkey. He received his PhD from Selcuk University, Turkey in the field of computer engineering. He has to his name more than 100 publications, including articles, authored and edited books, proceedings, and reports. He is also one of the Series Editors of the Biomedical and Robotics Healthcare Series from 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. Deepak Gupta is an eminent academician; plays versatile roles and responsibilities juggling between lectures, research, publications, consultancy, community service, PhD and post-doctorate supervision. With 12 years of rich expertise in teaching and two years in industry; he focuses on rational and practical learning. He has contributed important literature in the fields of Human-Computer Interaction, Intelligent Data Analysis, Nature-Inspired Computing, Machine Learning and Soft Computing. He is an Assistant Professor at Maharaja Agrasen Institute of Technology, Delhi, India. He has completed his Post-Doc from Inatel, Brazil, and Ph.D. from Dr. APJ Abdul Kalam Technical University. He has served as Editor-in-Chief, Guest Editor, and Associate Editor in SCI and various other reputed journals (Elsevier, Springer, Wiley & MDPI). He is currently a Post-Doc researcher at University of Valladolid, Spain. He has authored/edited a number of books, including Advanced Computational Techniques for Virtual Reality in Healthcare and Handbook of Computer Networks and Cyber Security: Principles and Paradigms from Springer, He has published 101 scientific research publications in reputed International Journals and Conferences including 49 SCI Indexed Journals of IEEE, Elsevier, Springer, Wiley and many more. He has also published one patent. He is Editor-in-Chief of Computers and Quantum Computing and Applications journal, Associate Editor of Expert Systems (Wiley), Intelligent Decision Technologies (IOS Press), Journal of Computational and Theoretical Nenoscience, and Honorary Editor of ICSES Transactions on Image Processing and Pattern Recognition. He is also a series editor of Intelligent Biomedical Data Analysis, De Gruyter (Germany).
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 Graduate Program on Telecommunication Engineering, Federal Institute of Education, Science and Technology of Ceará, Fortaleza/CE, Brazil.
He has a Ph.D in Mechanical Engineering from the Federal University of Paraíba (UFPB, 2010), an MSc in Teleinformatics Engineering from the Federal University of Ceará (UFC, 2007), and he graduated in Mechatronics Engineering at the Federal Center of Technological Education of Ceará (CEFETCE, 2006). He is a specialist, mainly, in Image Data Science, IoT, Machine/Deep Learning, Pattern Recognition, Robotic.
Dr. Ashish Khanna has 16 years of expertise in teaching, entrepreneurship, and research & development. He received his PhD degree from the National Institute of Technology, Kurukshetra, India. He has completed his Post-Doc from Internet of Things Lab at Inatel, Brazil. He has published around 40 SCI indexed papers in IEEE Transaction, Springer, Elsevier, Wiley and many more reputed Journals with cumulative impact factor of above 100. He has around 90 research articles in top SCI/ Scopus journals, conferences and book chapters. He is co-author/editor of numerous books, including Advanced Computational Techniques for Virtual Reality in Healthcare from Springer, Intelligent Data Analysis: From Data Gathering to Data Comprehension from Wiley, and Hybrid Computational Intelligence: Challenges and Applications from Elsevier. His research interests include Distributed Systems, MANET, FANET, VANET, IoT, and Machine Learning. He is one of the founders of Bhavya Publications and Universal Innovator Lab. Universal Innovator is actively involved in research, innovation, conferences, startup funding events and workshops. He is currently working at the Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology, Delhi, India and is also a Visiting Professor at the University of Valladolid, Spain.










Altre Informazioni

ISBN:

9780323907699

Condizione: Nuovo
Dimensioni: 235 x 191 mm
Formato: Brossura
Illustration Notes:Approx. 100 illustrations
Pagine Arabe: 812


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