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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.
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.
Chapter 1
Deep Learning for COVID-19 Infection’s Diagnosis, Prevention, and Treatment
Chapter 2
Artificial Intelligence in Coronavirus Detection—Recent Findings and Future Perspectives
Chapter 3
Solutions of Differential Equations for Prediction of COVID-19 Cases by Homotopy Perturbation Method
Chapter 4
Predictive Models of Hospital Readmission Rate Using the Improved AdaBoost in COVID-19
Chapter 5
Nigerian Medical Laboratory Diagnosis of COVID-19; from Grass to Grace
Chapter 6
COVID-19 CT Image Segmentation and Detection: Review
Chapter 7
Interactive Medical Chatbot for Assisting with COVID-related Queries
Chapter 8
COVID-19 Outbreak Prediction After Lockdown, Based on Current Data Analytics
Chapter 9
A Deep Learning CNN Model for Genome Sequence Classification
Chapter 10
The Impact of Lockdown Strategies on COVID-19 Cases with a Confined Sentiment Analysis of COVID-19 Tweets
Chapter 11
A Mathematical Model and Forecasting of COVID-19 Outbreak in India
Chapter 12
Automatic Lung Infection Segmentation of COVID-19 in CT Scan Images
Chapter 13
A Review of Feature Selection Algorithms in Determining the Factors Affecting COVID-19
Chapter 14
Industry 4.0 Technology-based Diagnosis for COVID-19
Index
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.
Amjad Rehman 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.
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