Diagnosis and Analysis of Covid-19 Using Artificial Intelligence and Machine Learning-based Techniques

Diagnosis and Analysis of COVID-19 using Artificial Intelligence and Machine Learning-Based Techniques offers new insights and demonstrates how machine learning (ML), artificial intelligence (AI), and (Internet of Things (IoT) can be used to diagnose and fight COVID-19 infection. Sections also discuss the challenges we face in using these technologies. Chapters cover pathogenesis, transmission, diagnosis, and treatment strategies for COVID-19, Artificial Intelligence and Machine Learning, and Blockchain /IoT Blockchain technology, examining how AI can be applied as a tool for detection and containment of the spread of COVID-19, and on the socioeconomic and educational post-pandemic impacts of the disease.

This is a multidisciplinary resource for those engaged in researching COVID-19 and how emerging technologies are being used as tools for detection, transmission and treatment strategies.

• Describes the molecular basis of pathogenesis, epidemiology, transmission mechanism, diagnostic approaches, and the mutational landscape of SARS-CoV-2
• Provides insights into post COVID-19 symptoms and consequences
• Demonstrates how machine learning, AI, and IoT is used to diagnose and fight COVID-19 infection
• Examines the use of Blockchain technology/IoT and interpretation and validation of data obtained from artificial intelligence

Mohammad Sufian Badar, PhD, is a Professor (temporary) in the Department of Computer Science and Engineering, SEST, Jamia Hamdard, New Delhi, India. Previously, he was Senior Teaching Faculty at UC Riverside, CA, United States, and an Analytics Architect at CenturyLink in Denver, CO, United States. He holds an MS in Molecular Science and Nanotechnology and a PhD in Engineering from Lusiana Tech University. Before that, he earned an MSc. in Bioinformatics from Jamia Millia Islamia, New Delhi. With over 18 years of teaching, research, and industry experience, Dr. Sufian has published in conferences and journals, authored chapters on AI, ML, Blockchain, IoT, Computational Biology, and has six books with Elsevier, Springer, and Bentham. His area of interest is in AI, ML, Computational Biology, and the integration of AI/ML with Health Sciences.

Nima Rezaei, MD, PhD, is Professor of Clinical Immunology and Allergy at Tehran University of Medical Sciences, where he also serves as Associate Dean of International Affairs for the School of Medicine and Director of the Global Academic Program. He is Deputy President of the Research Center for Immunodeficiencies and holds an affiliated research appointment in the Division of Clinical Immunology, Department of Laboratory Medicine, Karolinska Institutet, Sweden. He earned his MD from Tehran University of Medical Sciences and his PhD in Clinical Immunology and Human Genetics from the University of Sheffield, United Kingdom. His research addresses primary immunodeficiencies and translational immunology, with recent work extending into computational and AI-based approaches to immune profiling. He is the founder and President of the Universal Scientific Education and Research Network (USERN) and serves as co-editor of the Springer Nature series Advances in Experimental Medicine and Biology.

Dr. Imtiyaz Hassan is another bioinformatician from India who is currently working as an Assistant Professor at a Premier Central University, Jamia Millia Islamia (JMI), New Delhi. He has completed his Ph.D. from All India Institute of Medical Sciences (AIIMS). He was ranked 6 on the list of best Bioinformaticians in India. He was also appointed as a Postdoctoral fellow at Saint Louis University School of Medicine, USA. He has published more than 70 research articles in reputed international journals and has been serving as an Editorial Board Member of Journal of Protein and Proteomics, Journal of Natural Science, Biology and Medicine and many other journals. His thrust area of research is structure-based drug designing aimed to identify novel therapeutic agents. His research group is dedicated to understanding the structure-function relationships and try to develop methods to determine, analyze and exploit the structure of proteins and their complexes. Currently, he is involved in developing potential inhibitors against cancer and diabetes, and search to find anti-obesity agents in humans.

Dr. Jawed Ahmed is an Assistant Professor in the Department of Computer Science and Engineering at Hamdard University. His current research interest lies in Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT). He is also a Co-Chair ICT For Digital, Smart, and Sustainable Development International Conference

Professor M. Afshar Alam is presently working as Vice-Chancellor and Professor and Dean of School of Engineering Sciences and Technology at Jamia Hamdard, New Delhi. His research areas include Software Re-engineering, Data Mining, Bio-Informatics, Fuzzy databases, and Sustainable Development. He has authored 10 books, supervised more than 30 Doctoral students and more than 200 Post Graduate research projects and has more than 160 research papers in reputed journals to his credit. He is conferred with many prestigious awards like Bharat Samaj Ratna Award, AMP Award for Excellence in Education, Cooperative Citizen Award, World Environment Day Award, and Spardha Shree Award. He is also the member of various government bodies at both National and International level including University Grants Commission (UGC), All India Council of Technical Education (AICTE), National Assessment and Accreditation Council (NAAC), Department of Science & Technology (DST).