Researches and Applications of Artificial Intelligence to Mitigate Pandemics: History, Diagnostic Tools, Epidemiology, Healthcare, and Technology offers readers an interdisciplinary view of state-of-art research related to the COVID-19 outbreak, with a focus on tactics employed to model the number of cases of COVID-19 (time series modeling), models employed to diagnostics COVID-19 based on images, and the panoramic of COVID-19 since its discovery and up to this book's publication. This book showcases the algorithms and models available to manage pandemic data, the role of AI, IoT and Mathematical Modeling, how to prevent and fight COVID-19, and the existing medical, social and pharmaceutical support.
Chapters cover methods and protocols, the basics and history of diseases, the fast diagnosis of disease with different automated algorithms and artificial intelligence tools and techniques, the methods of handling epidemiology for mitigating the spread of disease, artificial intelligence and mathematical modeling techniques, and how mental and physical health is affected with social media usage.
- Explains novel and hybrid high quality artificial intelligence methodologies, techniques, algorithms, architectures, tools and methods to cope with pandemics
- Covers rapid point-of-care diagnostics, presents details on varied mathematical models developed to control epidemiology, and lists existing measures to disseminate the spread of infection using computational methods
- Highlights the negative effect of social media and other sources by applying preventive measures to combat depression and anxiety
Kauser Hameed, is a lecturer at King Faisal University –College of Computer Science - Information’s System department. She earned her Bachelor’s degree in Computer's Application from Osmania University, India in 2002 and completed her Master levels in Computer’s Application from the same campus in 2004. In more than a decade of her work experience, she hold promising and vivid work roles in multinational IT sectors such as GE Capitals and Sumtotal, while devoting her services in Academic later to that. Editing books, participating chapters and compiling academic videos is also one of her interesting diversions.
Surbhi Bhatia Khan is Doctorate in Computer Science and Engineering in the area of Machine
Learning and Social Media Analytics. She earned Project Management Professional Certification
from reputed Project Management Institute, USA. She is currently working in the Department of
Data Science, School of Science, Engineering and Environment, University of Salford, Manchester,
United Kingdom. She has more than 11 years of academic and teaching experience in different universities. She is the awardee of the Research Excellence award given by King Faisal University, Saudi Arabia, in 2021. She has published 100þ papers in many reputed journals in high indexed outlets. She has around 12 international patents from India, Australia, and the United States. She has successfully authored 3 books and has also edited 12 books. She has completed many projects approved from Ministry of Education, Saudi Arabia, and Deanship of Scientific Research in different universities in Saudi Arabia and from India. Her area of interest is Knowledge Management, Information Systems, Machine Learning, and Data Science.
Syed Tousif Ahmed holds a Masters of Computer Science and Engineering; graduated from Jawaharlal Nehru Technological University Hyderabad, India. His expertise lend strong hands on to High Performance Computing, Artificial Intelligence, Cloud database, Python, Linux administration and Data Science. Holding over 10 plus years of work experience in the field of Information Technology, he played vivid roles as working in Academics as well as in the industry. In his career journey he worked as a Database Administrator in University of Dammam, Oracle HR consultant at Extra Zonic Dammam, R and D associate at various funded research projects at renowned universities internationally and proved to show distinguished results. Currently, he is aspiring to pursue doctorate in one of his engrossing areas.
