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

Table of Contents

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- COVID-19
36. COVID-19: Monitoring the pandemic in India
37. Potential Antiviral Therapies for Corona Virus Disease (COVID-19)

Authors

Utku Kose Associate Professor, Department of Computer Engineering, S�leyman Demirel University, Isparta, Turkey. Dr. Utku Kose is an Associate Professor at S�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 Deep Learning for Medical Decision Support Systems, Springer; Artificial Intelligence Applications in Distance Education, IGI Global; Smart Applications with Advanced Machine Learning and Human-Centered Problem Design, Springer; Artificial Intelligence for Data-Driven Medical Diagnosis, DeGruyter; Computational Intelligence in Software Modeling, DeGruyter; Data Science for Covid-19, Volumes 1 and 2, Elsevier/Academic Press; and Deep Learning for Medical Applications with Unique Data, Elsevier/Academic Press, among others. Dr. Kose is a Series Editor of the Biomedical and Robotics Healthcare series from Taylor & Francis/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. Deepak Gupta Assistant Professor, Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology, Delhi, India.

Dr. Aditya Khamparia has expertise in teaching, entrepreneurship, and research and development of 11 years. He is presently working as Assistant Professor in Babasaheb Bhimrao Ambedkar University, Satellite Centre, Amethi, India. He received his Ph.D. degree from Lovely Professional University, Punjab, India in May 2018. He has completed his M. Tech. from VIT University, Vellore, Tamil Nadu, India and B. Tech. from RGPV, Bhopal, Madhya Pradesh, India. He has completed his PDF from UNIFOR, Brazil. He has published around 105 research papers along with book chapters including more than 25 papers in SCI indexed Journals with cumulative impact factor of above 100 to his credit. Additionally, he has authored and edited eleven books. Furthermore, he has served the research field as a Keynote Speaker/Session Chair/Reviewer/TPC member/Guest Editor and many more positions in various conferences and journals. His research interest include machine learning, deep learning for biomedical health informatics, educational technologies, and computer vision.

Victor Hugo Costa de Albuquerque Professor and Senior Researcher, Federal University of Ceara, Fortaleza, Graduate Program on Teleinformatics Engineering,Fortaleza/CE, Brazil. 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 Cear�, Brazil, and at the Graduate Program on Telecommunication Engineering, Federal Institute of Education, Science and Technology of Cear�, Fortaleza/CE, Brazil.
He has a Ph.D in Mechanical Engineering from the Federal University of Para�ba (UFPB, 2010), an MSc in Teleinformatics Engineering from the Federal University of Cear� (UFC, 2007), and he graduated in Mechatronics Engineering at the Federal Center of Technological Education of Cear� (CEFETCE, 2006). He is a specialist, mainly, in Image Data Science, IoT, Machine/Deep Learning, Pattern Recognition, Robotic. Ashish Khanna Sr. Assistant Professor, Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology (MAIT), New Delhi, India. Dr. Ashish Khanna has 16 years of expertise in teaching, entrepreneurship, and research and development. He received his PhD from the National Institute of Technology, Kurukshetra, India, and completed a post-doc degree at the National Institute of Telecommunications (Inatel), Brazil. He has published around 40 SCI-indexed papers in 'IEEE Transactions', and in other reputed journals by Springer, Elsevier, and Wiley, with a cumulative impact factor of above 100. He has published around 90 research articles in top SCI/Scopus journals, conferences, and book chapters. He is co-author or editor of numerous books, including 'Advanced Computational Techniques for Virtual Reality in Healthcare' (Springer), 'Intelligent Data Analysis: From Data Gathering to Data Comprehension' (Wiley), and 'Hybrid Computational Intelligence: Challenges and Applications' (Elsevier). His research interests include distributed systems, MANET, FANET, VANET, Internet of Things, and machine learning. He is one of the founders of Bhavya Publications and the Universal Innovator Lab, which is actively involved in research, innovation, conferences, start-up funding events, and workshops. He is currently working at the Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology, New Delhi, India, and is also a Visiting Professor at the University of Valladolid, Spain.