Intelligent Data Analysis for COVID-19 Pandemic

Chapter 1. Machine Learning Based Ensemble Approach for Predicting the Mortality Risk of Covid-19 Patients: A Case Study.- Chapter 2. The Role of Internet of Health Things (IoHTs) & Innovative Internet of  5G Medical Robotic Things (IIo-5GMRTs) in COVID-19 Global Health Risk Management and Logistics Planning.- Chapter 3. Battling COVID-19 with Process Model of Integrated Digital Technology: An Analysis of Qualitative Data.- Chapter 4. High-fidelity intelligence ventilator to help infect with Covid-19 based on artificial intelligence.- Chapter 5. Boon of Artificial Intelligence in Diagnosis of Covid-19.- Chapter 6. Artificial Intelligence and Big Data Solutions for COVID-19.- Chapter 7. Modeling the Transmition Dynamics of COVID-19 Virus Disease in Nigeria.- Chapter 8. Emerging Trends in Higher Education during Pandemic Covid-19: An impact study From West Bengal.- Chapter 9. COVID-19: Virology, Epidemiology, Diagnostics and Predictive modelling.- Chapter 10. Improved Estimation inLogistic Regression through Quadratic Bootstrap Approach: An Application in Indian Agricultural e-learning System during COVID-19 Pandemic.- Chapter 11. COVID-19 and Stock Markets: Deaths and Strict Policies.- Chapter 12. Artificial Intelligence Techniques in Medical Imaging for Detection of Corona Virus (COVID-19 / SARS-COV-2): A Brief Survey.- Chapter 13. A Travelling Disinfection-man Problem (TDP) for COVID-19: A Nonlinear Binary Constrained Gaining-Sharing knowledge-based Optimization Algorithm.- Chapter 14. COVID-19 Lock down Impact on Mental Health: A Cross-sectional Online Survey from Kerala, India.- Chapter 15. Analysis, Modelling and Prediction of COVID-19 Outbreaks using Machine Learning Algorithms.

Dr. Niranjanamurthy M is Assistant Professor, Department of Computer Applications, M S Ramaiah Institute of Technology, Bangalore, Karnataka, India. He completed Ph.D. in Computer Science at JJTU, Rajasthan (2016); M.Phil. in Computer Science at VMU, Salem (2009); Masters in Computer Applications at Visvesvaraiah Technological University, Belgaum, Karnataka (2007);   BCA from Kuvempu University 2004 with University 5th Rank. He has 10 years of teaching experience and 2 years of industry experience as Software Engineer. He has published books in Scholars Press Germany and CRC Press. He also published 56 research papers and filed 12 patents. Currently, he is guiding four Ph.D. research scholars in the areas of data science, edge computing, ML, and networking. He is Reviewer of 22 international journals and Series Editor in CRC Press and Scrivener Publishing. He has received best research journal reviewer and researcher awards. He is a member of IEEE, CSTA, IAENG, and INSC. His areas of interest are data science, ML, edge computing, software engineering, web services, cloud computing, and networking.

 

Dr. Siddhartha Bhattacharyya [LFOSI, LFISRD, FIET (UK), FIETE, FIE(I), SMIEEE, SMIETI, SMACM, LMCRSI, LMCSI, LMISTE, LMIUPRAI, LMCEGR, LMICCI, LMALI, MIRSS, MIAENG, MCSTA, MIAASSE, MIDES, MISSIP, MSDIWC] is currently serving as Professor in the Department of Computer Science and Engineering of Christ University, Bangalore. He is Co-Author of 5 books and Co-Editor of 75 books and has more than 300 research publications in international journals and conference proceedings to his credit. He has got two PCTs to his credit. He is Associate Editor of several reputed journals including Applied Soft Computing, IEEE Access, Evolutionary Intelligence, and IET Quantum Communications. He is Editor of International Journal of Pattern Recognition Research and  Founding Editor-in-Chief of International Journal of Hybrid Intelligence,

"Each article is self-contained with a detailed description of each method, background information, statistics and mathematical details, theory, and application. Anyone looking for inspiration could find several examples and use cases of available data that can be used for insight generation. ... The strength of this edited book is that the readers would become familiar with several data sources and demonstration of intelligent analysis of data that social scientist routinely collect." (Enayet Raheem, ISCB News, iscb.info, June, 2022)