Covid 19 Prediction Decision Making And Its Impacts

The book aims to outline the issues of AI and COVID-19, involving predictions,medical support decision-making, and possible impact on human life. Starting withmajor COVID-19 issues and challenges, it takes possible AI-based solutions forseveral problems, such as public health surveillance, early (epidemic) prediction,COVID-19 positive case detection, and robotics integration against COVID-19.Beside mathematical modeling, it includes the necessity of changes in innovationsand possible COVID-19 impacts. The book covers a clear understanding of AI-driven tools and techniques, where pattern recognition, anomaly detection, machinelearning, and data analytics are considered. It aims to include the wide range ofaudiences from computer science and engineering to healthcare professionals.

COVID-19 has hit the world unprepared, as the deadliest pandemic of the century. Governments and authorities, as leaders and decision makers fighting the virus, enormously tap into the power of artificial intelligence and its predictive models for urgent decision support. This book showcases a collection of important predictive models that used during the pandemic, and discusses and compares their efficacy and limitations. Readers from both healthcare industries and academia can gain unique insights on how predictive models were designed and applied on epidemic data. Taking COVID19 as a case study and showcasing the lessons learnt, this book will enable readers to be better prepared in the event of virus epidemics or pandemics in the future.

This book presents best practices involving applications of decision sciences, business tactics and behavioral sciences for COVID-19. Addressing concrete problems in these vital fields, it focuses on theoretical and methodological investigations of managerial decisions that drive production and service enterprises’ productivity and success. Moreover, it presents optimization techniques and tools that can also be adopted for other applications in various research areas after a thorough analysis of the specific problem. The book is intended for researchers and practitioners seeking optimum solutions to real-life problems in various application areas concerning COVID-19, helping them make scientifically founded decisions.

The book presents advanced AI based technologies in dealing with COVID-19 outbreak and provides an in-depth analysis of variety of COVID-19 datasets throughout globe. It discusses recent artificial intelligence based algorithms and models for data analysis of COVID-19 symptoms and its possible remedies. It provides a unique opportunity to present the work on state-of-the-art of modern artificial intelligence tools and technologies to track and forecast COVID-19 cases. It indicates insights and viewpoints from scholars regarding risk and resilience analytics for policy making and operations of large-scale systems on this epidemic. A snapshot of the latest architectures, frameworks in machine learning and data science are also highlighted to gather and aggregate data records related to COVID-19 and to diagnose the virus. It delivers significant research outcomes and inspiring new real-world applications with respect to feasible AI based solutions in COVID-19 outbreak. In addition, it discusses strong preventive measures to control such pandemic.

This book presents a compilation of the most recent implementation of artificial intelligence methods for solving different problems generated by the COVID-19. The problems addressed came from different fields and not only from medicine. The information contained in the book explores different areas of machine and deep learning, advanced image processing, computational intelligence, IoT, robotics and automation, optimization, mathematical modeling, neural networks, information technology, big data, data processing, data mining, and likewise. Moreover, the chapters include the theory and methodologies used to provide an overview of applying these tools to the useful contribution to help to face the emerging disaster. The book is primarily intended for researchers, decision makers, practitioners, and readers interested in these subject matters. The book is useful also as rich case studies and project proposals for postgraduate courses in those specializations.

Social and physical distancing and restrictions on international travel (thereafter “social and movement measures”) have been introduced to reduce the risk of acquiring or spreading infection with COVID-19 in various community settings. Whilst the risk of infection to COVID-19 decreases, social and movement measures exacerbate the economic slowdown and can worsen socioeconomic inequalities. Calibrating social and movement measures is complex as it has direct and indirect health and economic impacts, across different subpopulations, now and in the future, and is characterized by uncertainty, urgency, need for multiple levels of decision-making. In this type of context, there is no one-size-fits-all strategy. But inclusive decision making, systematically informed by data and communicated clearly will promote transparency in the process, increase the legitimacy of the decisions and promote trust between the population and the decision-makers. The World Health Organization and the Organisation for Economic Co-operation and Development describe, in their joint publication, a decision framework to assist countries as they continue to calibrate social and movement measures until there is widespread population coverage with the vaccine.

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data

COVID-19 is the most challenging crisis the world has faced for almost a century. As a truly global pandemic, there is not a single country on earth – or even a single person – immune to the economic, political and social impact of the devastating virus. This book analyses the coronavirus crisis in unparalleled depth. The author begins in section one by framing the COVID-19 pandemic by categorically identifying variables and factors central to understanding how COVID-19 has panned out. This is followed in section two with an examination of the pandemic in the realms of politics, public health and economics .Section three comprises in-depth country case studies, complete with scenario mapping and a formulation of recommendations, before section four looks beyond the immediate imperatives of the ongoing pandemic and pictures our shared future in a 'post-Covid' world. Confronting COVID-19's combination of rigorous, evidence-based analyses, projections and actionable recommendations makes this a must-read book for all leaders and decision makers in public, private and community sectors. Most of all, the ideas presented within these pages command the urgent attention of those within the international policy-making community.