Intelligent Computing Applications for COVID-19 : Predictions, Diagnosis, and Prevention book cover
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Intelligent Computing Applications for COVID-19
Predictions, Diagnosis, and Prevention

Edited By

Tanzila Saba

,

AR Khan



  • Available for pre-order. Item will ship after August 9, 2021
ISBN 9780367692476
August 9, 2021 Forthcoming by CRC Press
344 Pages 128 B/W Illustrations

 
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Book Description

Accurate estimation, diagnosis, and prevention of COVID-19 is a global challenge for healthcare organizations. Innovative measures can introduce and implement AI, and Mathematical Modeling applications. This book provides insight into the recent advances of applications, statistical methods, and mathematical modeling for the healthcare industry.

This book covers the state-of-the-art applications of AI and Machine Learning in past epidemics, pandemics, and COVID-19. It offers recent global case studies, and discusses how AI and statistical methods, initiatives, and applications such as Machine Learning, Deep Learning, Correlation and Regression Analysis play a major role in the prediction, diagnosis, and prevention of a pandemic. It will also focus on how AI and statistical applications can facilitate and restructure the healthcare system.

This book is written for Researchers, Students, Professionals, Executives, and the general public.

Table of Contents

Part 1: Prediction of COVID-19. 1. AI Future Applications and Challenges for COVID-19. 2. Mathematical Modeling Techniques for COVID-19. 3. Mathematical Predictive Modeling of COVID-19. 4. Machine Learning Based Predictive Modeling of COVID-19. 5. Statistical Methods for COVID-19 Prediction. 6. Emerging Computational Models Development for COVID-19. 7. Advanced Manufacturing and Digital Information Technologies for COVID-19 Prediction. 8. Case Study on Statistical and Mathematical Modeling Method for COVID-19 prediction. Part 2: Diagnosis of COVID-19. 9. Models for Diagnosis of COVID-19. 10. AI Strategies for Diagnosis of COVID-19. 11. Current Applications of Artificial Intelligence for COVID-19. 12. Case Study on the different Global Prevention Policies of COVID-19. 13. Industry 4.0 Technologies-Bbased Diagnosis for COVID-19. 14. Case Study on the State-of-the-Art AI Applications and Future of AI for COVID-19. 15. Laboratory Diagnosis of COVID-19. Part 3: Prevention of COVID-19. 16. Automated Self Precautionary Measure of COVID-19. 17. Individual, Family, and Interpersonal Correlation Analysis for COVID-19 Prevention. 18. AI Monitoring Application for Social Distancing in COVID-10 Emergency. 19. Case Study on Artificial Intelligence Applications for COVID-19 Prevention. 20. Statistical Methods for COVID-19 Prevention. 21. COVID -19 Prevention Strategies for Healthcare Staff, Students, Children. 22. Case Study on the State-of-the-Art AI Applications and Future of AI for COVID-19 Prevention.

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Editor(s)

Biography

Tanzila Saba earned her PhD in document information security and management from Faculty of Computing, UniversitiTeknologi Malaysia (UTM), Malaysia in 2012. She won the best student award in the School of Computing UTM for 2012. Currently, she is serving as an Associate Chair of Information Systems Department in the College of Computer and Information Sciences Prince Sultan University Riyadh KSA. Her primary research focus in recent years is Medical Imaging, Pattern Recognition, Data Mining, MRI analysis, and Soft-computing. She has above two hundred publications that have above 5000 citations. Her mostly publications are in biomedical research published in ISI/SCIE indexed. Due to her excellent research achievement, she is included in Marquis Who’s Who (S & T) 2012." Currently, she is an editor and reviewer of reputed journals and on the panel of TPC of international conferences. She led several funded research projects as a PI. She has full command of a variety of subjects and taught several courses at the graduate and postgraduate levels. On the accreditation side, she is a skilled lady with ABET& NCAAA quality assurance. She is the senior member of IEEE. Dr.Tanzila is the leader of the Artificial Intelligence& Data Analytics Research Lab at PSU and active professional members of ACM, AIS and IAENG organizations. She is the PSU WiDS (Women in Data Science) ambassador at Stanford University and Global WomenTech Conference. She earned the Best Researcher award at PSU for consecutive 4 years. She has been nominated as a Research Professor at PSU since September 2019.

AR Khan is a Senior Researcher in the Artificial Intelligence & Data Analytics Lab, Prince Sultan University, Riyadh, Saudi Arabia. He earned PhD & Postdoc from School of Computing Universiti Teknologi Malaysia, Malaysia specialization in Forensic Documents Analysis and Security with honor in 2010 and 2011 respectively. He received Rector award 2010 for best student in the university. His keen interests are in Data Mining, Health Informatics, Pattern Recognition. He is author of more than 200 ISI journal papers, conferences and is a senior member of IEEE. Currently, he is PI in several funded projects and also completed projects funded from MOHE Malaysia, Saudi Arabia.