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

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.

Artificial Intelligence for COVID-19
Artificial Intelligence for COVID-19

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.

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

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 in Healthcare
Artificial Intelligence in Healthcare

Author: Adam Bohr

Publisher: Academic Press

Published: 2020-06-21

Total Pages: 385

ISBN-13: 0128184396

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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

Prognosis Research in Healthcare
Prognosis Research in Healthcare

Author: Richard D. Riley

Publisher: Oxford University Press

Published: 2019-01-17

Total Pages: 373

ISBN-13: 0192516655

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"What is going to happen to me?" Most patients ask this question during a clinical encounter with a health professional. As well as learning what problem they have (diagnosis) and what needs to be done about it (treatment), patients want to know about their future health and wellbeing (prognosis). Prognosis research can provide answers to this question and satisfy the need for individuals to understand the possible outcomes of their condition, with and without treatment. Central to modern medical practise, the topic of prognosis is the basis of decision making in healthcare and policy development. It translates basic and clinical science into practical care for patients and populations. Prognosis Research in Healthcare: Concepts, Methods and Impact provides a comprehensive overview of the field of prognosis and prognosis research and gives a global perspective on how prognosis research and prognostic information can improve the outcomes of healthcare. It details how to design, carry out, analyse and report prognosis studies, and how prognostic information can be the basis for tailored, personalised healthcare. In particular, the book discusses how information about the characteristics of people, their health, and environment can be used to predict an individual's future health. Prognosis Research in Healthcare: Concepts, Methods and Impact, addresses all types of prognosis research and provides a practical step-by-step guide to undertaking and interpreting prognosis research studies, ideal for medical students, health researchers, healthcare professionals and methodologists, as well as for guideline and policy makers in healthcare wishing to learn more about the field of prognosis.

How to Prevent the Next Pandemic
How to Prevent the Next Pandemic

Author: Bill Gates

Publisher: Vintage

Published: 2022-05-03

Total Pages: 235

ISBN-13: 0593534492

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Governments, businesses, and individuals around the world are thinking about what happens after the COVID-19 pandemic. Can we hope to not only ward off another COVID-like disaster but also eliminate all respiratory diseases, including the flu? Bill Gates, one of our greatest and most effective thinkers and activists, believes the answer is yes. The author of the #1 New York Times best seller How to Avoid a Climate Disaster lays out clearly and convincingly what the world should have learned from COVID-19 and what all of us can do to ward off another catastrophe like it. Relying on the shared knowledge of the world’s foremost experts and on his own experience of combating fatal diseases through the Gates Foundation, Gates first helps us understand the science of infectious diseases. Then he shows us how the nations of the world, working in conjunction with one another and with the private sector, how we can prevent a new pandemic from killing millions of people and devastating the global economy. Here is a clarion call—strong, comprehensive, and of the gravest importance.

The Nature of Statistical Learning Theory
The Nature of Statistical Learning Theory

Author: Vladimir Vapnik

Publisher: Springer Science & Business Media

Published: 2013-06-29

Total Pages: 324

ISBN-13: 1475732643

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The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning as a general problem of function estimation based on empirical data. Omitting proofs and technical details, the author concentrates on discussing the main results of learning theory and their connections to fundamental problems in statistics. This second edition contains three new chapters devoted to further development of the learning theory and SVM techniques. Written in a readable and concise style, the book is intended for statisticians, mathematicians, physicists, and computer scientists.

Patient Care Under Uncertainty
Patient Care Under Uncertainty

Author: Charles F. Manski

Publisher: Princeton University Press

Published: 2019-09-10

Total Pages: 184

ISBN-13: 0691194734

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For the past few years, the author, a renowned economist, has been applying the statistical tools of economics to decision making under uncertainty in the context of patient health status and response to treatment. He shows how statistical imprecision and identification problems affect empirical research in the patient-care sphere.

Artificial Intelligence for Coronavirus Outbreak
Artificial Intelligence for Coronavirus Outbreak

Author: Simon James Fong

Publisher: Springer Nature

Published: 2020-06-22

Total Pages: 84

ISBN-13: 9811559368

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This book examines how the wonders of AI have contributed to the battle against COVID-19. Just as history repeats itself, so do epidemics and pandemics. In the face of the novel coronavirus disease, COVID-19, the book explores whether, in this digital era where artificial intelligence is successfully applied in all areas of industry, we are doing any better than our ancestors did in dealing with pandemics. One of the most contagious diseases ever known, COVID-19 is spreading like wildfire around and has cost thousands of human lives. The book discusses how AI can help fight this deadly virus, from early warnings, prompt emergency responses, and critical decision-making to surveillance drones. Serving as a technical reference resource, data analytic tutorial and a chronicle of the application of AI in epidemics, this book will appeal to academics, students, data scientists, medical practitioners, and anybody who is concerned about this global epidemic.

Global Trends 2040
Global Trends 2040

Author: National Intelligence Council

Publisher: Cosimo Reports

Published: 2021-03

Total Pages: 158

ISBN-13: 9781646794973

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"The ongoing COVID-19 pandemic marks the most significant, singular global disruption since World War II, with health, economic, political, and security implications that will ripple for years to come." -Global Trends 2040 (2021) Global Trends 2040-A More Contested World (2021), released by the US National Intelligence Council, is the latest report in its series of reports starting in 1997 about megatrends and the world's future. This report, strongly influenced by the COVID-19 pandemic, paints a bleak picture of the future and describes a contested, fragmented and turbulent world. It specifically discusses the four main trends that will shape tomorrow's world: - Demographics-by 2040, 1.4 billion people will be added mostly in Africa and South Asia. - Economics-increased government debt and concentrated economic power will escalate problems for the poor and middleclass. - Climate-a hotter world will increase water, food, and health insecurity. - Technology-the emergence of new technologies could both solve and cause problems for human life. Students of trends, policymakers, entrepreneurs, academics, journalists and anyone eager for a glimpse into the next decades, will find this report, with colored graphs, essential reading.