Bøger i Medical Virology: From Pathogenesis to Disease Control serien

This book provides a comprehensive overview of recent novel coronavirus (SARS-CoV-2) infection, their biology and associated challenges for their treatment and prevention of novel Coronavirus Disease 2019 (COVID-19). Discussing various aspects of COVID-19 infection, including global epidemiology, genome organization, immunopathogenesis, transmission cycle, diagnosis, treatment, prevention, and control strategies, it highlights host-pathogen interactions, host immune response, and pathogen immune invasion strategies toward developing an immune intervention or preventive vaccine for COVID-19.An understanding of the topics covered in the book is imperative in the context of designing strategies to protect the human race from further losses and harm due to SARS-CoV-2 infection causing COVID-19.

The book examines the role of artificial intelligence during the COVID-19 pandemic, including its application in i) early warnings and alerts, ii) tracking and prediction, iii) data dashboards, iv) diagnosis and prognosis, v) treatments, and cures, and vi) social control.

The book examines the role of artificial intelligence during the COVID-19 pandemic, including its application in i) early warnings and alerts, ii) tracking and prediction, iii) data dashboards, iv) diagnosis and prognosis, v) treatments, and cures, and vi) social control. It explores the use of artificial intelligence in the context of population screening and assessing infection risks, and presents mathematical models for epidemic prediction of COVID-19. Furthermore, the book discusses artificial intelligence-mediated diagnosis, and how machine learning can help in the development of drugs to treat the disease. Lastly, it analyzes various artificial intelligence-based models to improve the critical care of COVID-19 patients.

This book comprehensively reviews the potential of Artificial Intelligence (AI) in biomedical research and healthcare, with a major emphasis on virology. The initial chapter presents the applications of machine learning methods for structured data, such as the classical support vector machine and neural network, modern deep learning, and natural language processing for unstructured data in biomedical research and healthcare. The subsequent chapters explore the applications of AI in tackling COVID-19, analysis of the pandemic, viral infection, disease spread, and control. The book further identifies the potential applications of machine learning in the field of virology with a focus on the key aspects of infection: diagnosis, transmission, response to treatment, and resistance. The book also discusses progress and challenges in developing viral vaccines and examines the application of viruses in translational research and human healthcare.Furthermore, the book covers the applications of artificial intelligence-mediated diagnosis and the development of drugs to treat the disease. Towards the end, the book summarizes the ethical and legal challenges posed by AI in healthcare and biomedical research. This book is an invaluable source for researchers, medical and industry practitioners, academicians, and students exploring the applications of AI in biomedical research and healthcare.¿