Novel AI and Data Science Advancements for Sustainability in the Era of COVID-19
- 1st Edition - April 5, 2022
- Imprint: Academic Press
- Editors: Victor Chang, Mohamed Abdel-Basset, Muthu Ramachandran, Nicolas Green, Gary Wills
- Language: English
- Paperback ISBN:9 7 8 - 0 - 3 2 3 - 9 0 0 5 4 - 6
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 9 0 3 7 8 - 3
Novel AI and Data Science Advancements for Sustainability in the Era of COVID-19 discusses how the role of recent technologies applied to health settings can help fight virus out… Read more
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Request a sales quoteNovel AI and Data Science Advancements for Sustainability in the Era of COVID-19 discusses how the role of recent technologies applied to health settings can help fight virus outbreaks. Moreover, it provides guidelines on how governments and institutions should prepare and quickly respond to drastic situations using technology to support their communities in order to maintain life and functional as efficiently as possible. The book discusses topics such as AI-driven histopathology analysis for COVID-19 diagnosis, bioinformatics for subtype rational drug design, deep learning-based treatment evaluation and outcome prediction, sensor informatics for monitoring infected patients, and machine learning for tracking and prediction models.
In addition, the book presents AI solutions for hospital management during an epidemic or pandemic, along with real-world solutions and case studies of successful measures to support different types of communities. This is a valuable source for medical informaticians, bioinformaticians, clinicians and other healthcare workers and researchers who are interested in learning more on how recently developed technologies can help us fight and minimize the effects of global pandemics.
- Discusses AI advancements in predictive and decision modeling and how to design mobile apps to track contagion spread
- Presents the smart contract concept in blockchain and cryptography technology to guarantee security and privacy of people’s data once their information has been used to fight the pandemic
- Encompasses guidelines for emergency preparedness, planning, recovery and continuity management of communities to support people in emergencies like a virus outbreak
Researchers and graduate students on medical informatics; clinicians; healthcare providers. Data scientists
- Cover image
- Title page
- Table of Contents
- Copyright
- Contributors
- Chapter 1: Deep learning-based hybrid models for prediction of COVID-19 using chest X-ray
- Abstract
- 1: Introduction
- 2: Related work
- 3: Modeling
- 4: Experimental setup
- 5: Results and discussion
- 6: Conclusions
- References
- Chapter 2: Investigation of COVID-19 and scientific analysis big data analytics with the help of machine learning
- Abstract
- Acknowledgment
- 1: Introduction and background
- 2: Literature review
- 3: COVID-19 pandemic in the new era of big data analytics: Methodological innovations and future research directions
- 4: Review of big data analytics, artificial intelligence and nature-inspired computing models towards accurate detection of COVID-19 pandemic cases and contact tracing
- 5: Significant applications of big data in COVID-19 pandemic
- 6: Research problem
- 7: Research questions
- 8: Objectives
- 9: Methodology
- 10: Algorithm
- 11: Conclusion
- References
- Chapter 3: Designing a conceptual model in the artificial intelligence environment for the health care sector
- Abstract
- 1: Introduction
- 2: Background
- 3: Literature review
- 4: Approach suggested for designing a conceptual model
- 5: Selection of concepts in information and communication technology
- 6: Databases related to classification of diseases, digital image code, and viruses taxonomy
- 7: Role of core team
- 8: Overview of viruses
- 9: Covid-19
- 10: Case illustration based on the healthcare sector in India
- 11: Machine learning approach for analyzing the medical data
- 12: Indian environment
- 13: Academic research approach
- 14: Developing a drug
- 15: Discussion
- 16: Conclusion
- References
- Chapter 4: Augmented reality, virtual reality and new age technologies demand escalates amid COVID-19
- Abstract
- 1: Introduction
- 2: Updates ways to minimize infections
- 3: Background and literature review
- 4: Demand escalation of AR/VR due to COVID-19 pandemic
- 5: Conclusion
- References
- Chapter 5: Using interpretable machine learning identify factors contributing to COVID-19 cases in the United States
- Abstract
- 1: Introduction
- 2: Related work
- 3: Proposed approach
- 4: Experiment and results
- 5: Conclusion and future work
- References
- Chapter 6: Cloud-based data pipeline orchestration platform for COVID-19 evidence-based analytics
- Abstract
- 1: Challenges in COVID-19 data handling
- 2: Background and related works
- 3: OnTimeEvidence architecture and component implementation
- 4: OnTimeEvidence COVID-19 case study
- 5: Conclusion—What we have learnt?
- References
- Chapter 7: Threat model and security analysis of video conferencing systems as a communication paradigm during the COVID-19 pandemic
- Abstract
- Acknowledgments
- 1: Introduction
- 2: Background
- 3: Assets of video conferencing tools
- 4: Point of entry
- 5: Attack model
- 6: Threats and vulnerabilities
- 7: Mitigation strategies
- 8: Conclusion and future work
- References
- Chapter 8: Role of artificial intelligence in fast-track drug discovery and vaccine development for COVID-19
- Abstract
- 1: Introduction
- 2: Artificial intelligence in COVID-19
- 3: Artificial intelligence in drug discovery
- 4: Chemical structure input for data processing
- 5: Artificial intelligence in repositioning approaches
- 6: Artificial intelligence for accelerating computer modeling
- 7: Artificial intelligence: De novo design of novel small molecules
- 8: Artificial intelligence in protein structure prediction
- 9: Artificial intelligence in vaccine development
- 10: Summary
- 11: Conclusions and future directions
- References
- Chapter 9: The economic impact of covid-19 and the role of AI
- Abstract
- 1: Introduction
- 2: Economic impact of Covid-19
- 3: Artificial intelligence (AI) as a solace to help mankind out
- 4: Future scope of AI
- 5: Conclusion
- References
- Chapter 10: An optimized CNN based automated COVID-19 lung infection identification technique from C.T. images
- Abstract
- 1: Introduction
- 2: Literature review
- 3: Proposed system
- 4: Simulation results and discussion
- 5: Conclusion
- References
- Index
- Edition: 1
- Published: April 5, 2022
- No. of pages (Paperback): 298
- No. of pages (eBook): 298
- Imprint: Academic Press
- Language: English
- Paperback ISBN: 9780323900546
- eBook ISBN: 9780323903783
VC
Victor Chang
Victor Chang, PhD, is a Professor of Business Analytics at the Department of Operations and Information Management, Aston Business School, Aston University, UK. He will be involved in leading a New Research Centre. He has been a Full Professor of Data Science and Information Systems and Research Group leader at Teesside University. He was previously a Senior Associate Professor, Director of PhD and Director of MRes at International Business School Suzhou (IBSS), Xi’an Jiaotong-Liverpool University, China. He was also a very active and contributing key member at Research Institute of Big Data Analytics, XJTLU, and an Honorary Associate Professor at University of Liverpool. Before becoming an academic, he has achieved 97% on average in 27 IT certifications. He is Editor-in-Chief of IJOCI & OJBD journals, Associate Editor of IEEE TII, Information Fusion, and JGIM, Scientific Report, IJBSR and IDD journals. He is a founding and Conference Chair of IoTBDS, COMPLEXIS, FEMIB and IIoTBDSC conferences. He authored 5 books and edited 2 and is widely regarded as one of the most active and influential young scientist and expert in IoT/Data Science/Cloud/security/AI/IS, as he has experience to develop 10 different services for multiple disciplines.
Affiliations and expertise
Professor of Business Analytics, Department of Operations and Information Management, Aston Business School, Aston University, Birmingham, United KingdomMA
Mohamed Abdel-Basset
Dr. Mohamed Abdel-Basset is Associate Professor and Head of the Department of Computer Science, within the Faculty of Computers and Informatics, at Zagazig University, Egypt. He received his B.Sc., M.Sc and Ph.D in operations research at the Faculty of Computers and Informatics, Zagazig University. Dr. Abdel-Basset’s research interests are in Optimization, Operations Research, Data Mining, Computational Intelligence, Applied Statistics, Decision Support Systems, Robust Optimization, Engineering Optimization, Multiobjective Optimization, Swarm Intelligence, Evolutionary Algorithms, and Artificial Neural Networks. He is currently working on the application of multi-objective and robust meta-heuristic optimization techniques. Dr. Abdel-Basset is an Editor or Reviewer for several international journals and conferences, and has published more than 100 articles in international journals and conference proceedings.
Affiliations and expertise
Associate Professor, Faculty of Computers and Informatics, Zagazig University, EgyptMR
Muthu Ramachandran
Professor Muthu Ramachandran is currently a Cybersecurity, AI, and Blockchain Research Consultant at Forti5 Technologies, UK and a Professor Extraordinarius at University of South Africa (UNISA). Muthu is a certified IASME CE, ICA, IoT Cyber & IoT Assurance. Muthu is also an Editorial Board at Blockchain in Healthcare Today (BHTY, USA) and International Journal of Organizational and Collective Intelligence (IJOCI). Muthu has also been awarded as Top Blockchain Voices by LinkedIn. Previously, Muthu was a visiting Professor at Indian Institute of Technology (ISM) Dhanbad, India and at University of Southampton. Muthu has 35+ years of experiences in teaching & research in both academia and in industrial settings. Muthu was also an Associate Professor in the School of Built Environment, Engineering, and Computing at Leeds Beckett University in the UK for 18 years. Prior to his academic career, he spent nearly eight years in industrial research with Philips Research Labs, Volantis Systems Ltd, Surrey, UK, and at DRDO, Hyderabad, India as a Senior Scientist working on real-time systems, software architecture, reuse, and testing. Currently, Muthu has established several Software Engineering Frameworks: Software Security Engineering, Cybersecurity Engineering, AI Ethics and Quality, IoT SE, Cloud SE, Blockchain in Healthcare, etc.
Muthu has authored and co-authored numerous books, book chapters, journal articles, and conference papers, with significant contributions to the fields of computer science, software engineering, service computing, Agile SE, and Cloud software engineering. He is a recognized senior member of IEEE and ACM, a Fellow of BCS, and a Senior Fellow of Advance HE. Muthu has chaired and delivered keynote speeches at several conferences and workshops, including SE-CLOUD, SECE 2020 (IEEE COMPSAC), IoTBDS, DSC 2019-2022, and Complexis. He has actively participated in research projects across various domains of systems & software engineering, SPI for SMEs, emergency and disaster management systems, software components and architectures, software security engineering, and cloud computing.Affiliations and expertise
Cybersecurity, AI, and Blockchain Research Consultant at Forti5 Technologies, UK and a Professor Extraordinarius at University of South Africa (UNISA)NG
Nicolas Green
Nicolas G Green, PhD, is an Associate Professor in the School of Electronics and Computer Science at the University of Southampton, with research primarily focusing on design and development of technology and systems for Lab-on-a-Chip and Point of Care applications in medicine and environmental science. He is an expert on electrical and optical techniques for the detection, measurement, characterization, classification and separation of biological cells, bacteria, viruses and biomolecules. He is also developing strategies for the application of machine learning for assisting medical experts and practitioners in diagnoses.
Affiliations and expertise
Bioelectronics and Microfluidity, Electronics and Computer Science, University of Southampton, UKGW
Gary Wills
Gary Wills, PhD, research project focuses on Secure Systems Engineering and applications for industry, medicine, and FinTech. Dr. Wills’s work cross-discipline with colleagues from industry and academia. His research can be grouped under a number of themes: Machine learning, Internet of things, Blockchain, Security, Computational Finance, Data Protection, and Cloud Services. He has published widely on these topics, in books, book chapters, official reports, journal articles and conferences paper. Gary has co-edited a number of special issues, and regularly reviews articles for international journals.
Affiliations and expertise
Cyber Physical Research Group, Electronics and Computer Science, University of Southampton, UKRead Novel AI and Data Science Advancements for Sustainability in the Era of COVID-19 on ScienceDirect