Decision Sciences for COVID-19

Decision Sciences for COVID-19 PDF

Author: Said Ali Hassan

Publisher: Springer Nature

Published: 2022-02-28

Total Pages: 475

ISBN-13: 3030870197

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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.

COVID-19: Prediction, Decision-Making, and its Impacts

COVID-19: Prediction, Decision-Making, and its Impacts PDF

Author: K.C. Santosh

Publisher: Springer Nature

Published: 2020-12-11

Total Pages: 137

ISBN-13: 9811596824

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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.

Predictive Models for Decision Support in the COVID-19 Crisis

Predictive Models for Decision Support in the COVID-19 Crisis PDF

Author: Joao Alexandre Lobo Marques

Publisher: Springer Nature

Published: 2020-11-30

Total Pages: 103

ISBN-13: 3030619133

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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.

Artificial Intelligence for COVID-19

Artificial Intelligence for COVID-19 PDF

Author: Diego Oliva

Publisher: Springer Nature

Published: 2021-07-19

Total Pages: 594

ISBN-13: 3030697444

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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.

Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry

Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry PDF

Author: Chkoniya, Valentina

Publisher: IGI Global

Published: 2021-06-25

Total Pages: 653

ISBN-13: 1799869865

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The contemporary world lives on the data produced at an unprecedented speed through social networks and the internet of things (IoT). Data has been called the new global currency, and its rise is transforming entire industries, providing a wealth of opportunities. Applied data science research is necessary to derive useful information from big data for the effective and efficient utilization to solve real-world problems. A broad analytical set allied with strong business logic is fundamental in today’s corporations. Organizations work to obtain competitive advantage by analyzing the data produced within and outside their organizational limits to support their decision-making processes. This book aims to provide an overview of the concepts, tools, and techniques behind the fields of data science and artificial intelligence (AI) applied to business and industries. The Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry discusses all stages of data science to AI and their application to real problems across industries—from science and engineering to academia and commerce. This book brings together practice and science to build successful data solutions, showing how to uncover hidden patterns and leverage them to improve all aspects of business performance by making sense of data from both web and offline environments. Covering topics including applied AI, consumer behavior analytics, and machine learning, this text is essential for data scientists, IT specialists, managers, executives, software and computer engineers, researchers, practitioners, academicians, and students.

Predictive Models for Decision Support in the COVID-19 Crisis

Predictive Models for Decision Support in the COVID-19 Crisis PDF

Author: Joao Alexandre Lobo Marques

Publisher: Springer

Published: 2020-12-01

Total Pages: 98

ISBN-13: 9783030619121

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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.

Data Science for COVID-19 Volume 1

Data Science for COVID-19 Volume 1 PDF

Author: Utku Kose

Publisher: Academic Press

Published: 2021-05-20

Total Pages: 754

ISBN-13: 0128245379

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Data Science for COVID-19 presents leading-edge research on data science techniques for the detection, mitigation, treatment and elimination of COVID-19. Sections provide an introduction to data science for COVID-19 research, considering past and future pandemics, as well as related Coronavirus variations. Other chapters cover a wide range of Data Science applications concerning COVID-19 research, including Image Analysis and Data Processing, Geoprocessing and tracking, Predictive Systems, Design Cognition, mobile technology, and telemedicine solutions. The book then covers Artificial Intelligence-based solutions, innovative treatment methods, and public safety. Finally, readers will learn about applications of Big Data and new data models for mitigation. Provides a leading-edge survey of Data Science techniques and methods for research, mitigation and treatment of the COVID-19 virus Integrates various Data Science techniques to provide a resource for COVID-19 researchers and clinicians around the world, including both positive and negative research findings Provides insights into innovative data-oriented modeling and predictive techniques from COVID-19 researchers Includes real-world feedback and user experiences from physicians and medical staff from around the world on the effectiveness of applied Data Science solutions

Framework for Equitable Allocation of COVID-19 Vaccine

Framework for Equitable Allocation of COVID-19 Vaccine PDF

Author: National Academies of Sciences, Engineering, and Medicine

Publisher: National Academies Press

Published: 2020-11-30

Total Pages: 273

ISBN-13: 030968224X

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In response to the coronavirus disease 2019 (COVID-19) pandemic and the societal disruption it has brought, national governments and the international community have invested billions of dollars and immense amounts of human resources to develop a safe and effective vaccine in an unprecedented time frame. Vaccination against this novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), offers the possibility of significantly reducing severe morbidity and mortality and transmission when deployed alongside other public health strategies and improved therapies. Health equity is intertwined with the impact of COVID-19 and there are certain populations that are at increased risk of severe illness or death from COVID-19. In the United States and worldwide, the pandemic is having a disproportionate impact on people who are already disadvantaged by virtue of their race and ethnicity, age, health status, residence, occupation, socioeconomic condition, or other contributing factors. Framework for Equitable Allocation of COVID-19 Vaccine offers an overarching framework for vaccine allocation to assist policy makers in the domestic and global health communities. Built on widely accepted foundational principles and recognizing the distinctive characteristics of COVID-19, this report's recommendations address the commitments needed to implement equitable allocation policies for COVID-19 vaccine.

COVID-19

COVID-19 PDF

Author: Jie-Ming Qu

Publisher: Elsevier

Published: 2020-10-22

Total Pages: 114

ISBN-13: 0128242515

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COVID-19: The Essentials of Prevention and Treatment elaborates on the ethology, pathogenesis, epidemiology, clinical characteristics, treatment principles, rehabilitation and prevention, and prevention and control measures for COVID-19. Aimed at healthcare workers, and written to be a practical guide, six chapters cover the following aspects of COVID-19: respiratory viruses; pathogenesis; case definitions and diagnosis; treatment; prevention and disease control; and prospects for the management and research of respiratory virus infections. This book gives first-hand information on the prevention, control, diagnosis and treatment of COVID-19. COVID-19 was recognized as a pandemic in March 2020 by the World Health Organization. It is a disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Physicians working in China, particularly where the outbreak was first identified in Wuhan, have built up knowledge of prevention and control measures, and diagnosis and treatment of this disease. These insights are now globally relevant. The authors of this book are senior physicians specializing in respiratory diseases, pulmonary diseases and critical care medicine, and are all clinical and scientific research experts working in China, with particular experience in Wuhan. Describes the prevention, control, diagnosis and treatment of COVID-19 Offers practical guidance to healthcare professionals for COVID-19 Gives clinical insights in a question and answer format Details first-hand experience in Chinese cities during the initial outbreak Presents insights that healthcare professionals need to prevent, diagnose, and treat COVID-19

Epidemic Analytics for Decision Supports in COVID19 Crisis

Epidemic Analytics for Decision Supports in COVID19 Crisis PDF

Author: Joao Alexandre Lobo Marques

Publisher: Springer Nature

Published: 2022-05-20

Total Pages: 161

ISBN-13: 3030952819

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Covid-19 has hit the world unprepared, as the deadliest pandemic of the century. Governments and authorities, as leaders and decision makers fighting against the virus, enormously tap on the power of AI and its data analytics models for urgent decision supports at the greatest efforts, ever seen from human history. This book showcases a collection of important data analytics models that were used during the epidemic, and discusses and compares their efficacy and limitations. Readers who from both healthcare industries and academia can gain unique insights on how data analytics models were designed and applied on epidemic data. Taking Covid-19 as a case study, readers especially those who are working in similar fields, would be better prepared in case a new wave of virus epidemic may arise again in the near future.