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.

Artificial Intelligence and Machine Learning for COVID-19
Artificial Intelligence and Machine Learning for COVID-19

Author: Fadi Al-Turjman

Publisher: Springer

Published: 2021-02-17

Total Pages: 267

ISBN-13: 9783030601874

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This book is dedicated to addressing the major challenges in fighting COVID-19 using artificial intelligence (AI) and machine learning (ML) – from cost and complexity to availability and accuracy. The aim of this book is to focus on both the design and implementation of AI-based approaches in proposed COVID-19 solutions that are enabled and supported by sensor networks, cloud computing, and 5G and beyond. This book presents research that contributes to the application of ML techniques to the problem of computer communication-assisted diagnosis of COVID-19 and similar diseases. The authors present the latest theoretical developments, real-world applications, and future perspectives on this topic. This book brings together a broad multidisciplinary community, aiming to integrate ideas, theories, models, and techniques from across different disciplines on intelligent solutions/systems, and to inform how cognitive systems in Next Generation Networks (NGN) should be designed, developed, and evaluated while exchanging and processing critical health information. Targeted readers are from varying disciplines who are interested in implementing the smart planet/environments vision via wireless/wired enabling technologies.

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

Enabling Healthcare 4.0 for Pandemics
Enabling Healthcare 4.0 for Pandemics

Author: Abhinav Juneja

Publisher: John Wiley & Sons

Published: 2021-09-08

Total Pages: 352

ISBN-13: 111976906X

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ENABLING HEALTHCARE 4.0 for PANDEMICS The book explores the role and scope of AI, machine learning and other current technologies to handle pandemics. In this timely book, the editors explore the current state of practice in Healthcare 4.0 and provide a roadmap for harnessing artificial intelligence, machine learning, and Internet of Things, as well as other modern cognitive technologies, to aid in dealing with the various aspects of an emergency pandemic outbreak. There is a need to improvise healthcare systems with the intervention of modern computing and data management platforms to increase the reliability of human processes and life expectancy. There is an urgent need to come up with smart IoT-based systems which can aid in the detection, prevention and cure of these pandemics with more precision. There are a lot of challenges to overcome but this book proposes a new approach to organize the technological warfare for tackling future pandemics. In this book, the reader will find: State-of-the-art technological advancements in pandemic management; AI and ML-based identification and forecasting of pandemic spread; Smart IoT-based ecosystem for pandemic scenario. Audience The book will be used by researchers and practitioners in computer science, artificial intelligence, bioinformatics, data scientists, biomedical statisticians, as well as industry professionals in disaster and pandemic management.

Artificial Intelligence and Machine Learning in Public Healthcare
Artificial Intelligence and Machine Learning in Public Healthcare

Author: KC Santosh

Publisher: Springer Nature

Published: 2022-01-01

Total Pages: 93

ISBN-13: 9811667683

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This book discusses and evaluates AI and machine learning (ML) algorithms in dealing with challenges that are primarily related to public health. It also helps find ways in which we can measure possible consequences and societal impacts by taking the following factors into account: open public health issues and common AI solutions (with multiple case studies, such as TB and SARS: COVID-19), AI in sustainable health care, AI in precision medicine and data privacy issues. Public health requires special attention as it drives economy and education system. COVID-19 is an example—a truly infectious disease outbreak. The vision of WHO is to create public health services that can deal with abovementioned crucial challenges by focusing on the following elements: health protection, disease prevention and health promotion. For these issues, in the big data analytics era, AI and ML tools/techniques have potential to improve public health (e.g., existing healthcare solutions and wellness services). In other words, they have proved to be valuable tools not only to analyze/diagnose pathology but also to accelerate decision-making procedure especially when we consider resource-constrained regions.

Reprogramming the American Dream
Reprogramming the American Dream

Author: Kevin Scott

Publisher: HarperCollins

Published: 2020-04-07

Total Pages: 274

ISBN-13: 0062879898

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** #1 Wall Street Journal Bestseller ** In this essential book written by a rural native and Silicon Valley veteran, Microsoft’s Chief technology officer tackles one of the most critical issues facing society today: the future of artificial intelligence and how it can be realistically used to promote growth, even in a shifting employment landscape. There are two prevailing stories about AI: for heartland low- and middle-skill workers, a dystopian tale of steadily increasing job destruction; for urban knowledge workers and the professional class, a utopian tale of enhanced productivity and convenience. But there is a third way to look at this technology that will revolutionize the workplace and ultimately the world. Kevin Scott argues that AI has the potential to create abundance and opportunity for everyone and help solve some of our most vexing problems. As the chief technology officer at Microsoft, he is deeply involved in the development of AI applications, yet mindful of their potential impact on workers—knowledge he gained firsthand growing up in rural Virginia. Yes, the AI Revolution will radically disrupt economics and employment for everyone for generations to come. But what if leaders prioritized the programming of both future technology and public policy to work together to find solutions ahead of the coming AI epoch? Like public health, the space program, climate change and public education, we need international understanding and collaboration on the future of AI and work. For Scott, the crucial question facing all of us is this: How do we work to ensure that the continued development of AI allows us to keep the American Dream alive? In this thoughtful, informed guide, he offers a clear roadmap to find the answer.

Machine Learning and AI for Healthcare
Machine Learning and AI for Healthcare

Author: Arjun Panesar

Publisher: Apress

Published: 2019-02-04

Total Pages: 390

ISBN-13: 1484237994

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Explore the theory and practical applications of artificial intelligence (AI) and machine learning in healthcare. This book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare and big data challenges. You’ll discover the ethical implications of healthcare data analytics and the future of AI in population and patient health optimization. You’ll also create a machine learning model, evaluate performance and operationalize its outcomes within your organization. Machine Learning and AI for Healthcare provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of AI applications. These are illustrated through leading case studies, including how chronic disease is being redefined through patient-led data learning and the Internet of Things. What You'll LearnGain a deeper understanding of key machine learning algorithms and their use and implementation within wider healthcare Implement machine learning systems, such as speech recognition and enhanced deep learning/AI Select learning methods/algorithms and tuning for use in healthcare Recognize and prepare for the future of artificial intelligence in healthcare through best practices, feedback loops and intelligent agentsWho This Book Is For Health care professionals interested in how machine learning can be used to develop health intelligence – with the aim of improving patient health, population health and facilitating significant care-payer cost savings.

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.

Ethical Implications of Reshaping Healthcare With Emerging Technologies
Ethical Implications of Reshaping Healthcare With Emerging Technologies

Author: Musiolik, Thomas Heinrich

Publisher: IGI Global

Published: 2021-10-01

Total Pages: 242

ISBN-13: 1799878899

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Improving quality of life is one of the main advantages of integrating new innovations into medicine. New technologies are revolutionizing medicine and opening new opportunities for patients, doctors, clinics, and companies. The patient's well-being is monitored autonomously by smartphones, digital medical records simplify everyday clinical work, virtual reality is used for treatment, and robots help in the operating room. The new technological possibilities in healthcare not only change patients’ lives, but also the work of doctors, clinics, and companies. In the fields of healthcare and medicine, new technologies can be used for patient communication, health monitoring, or for the treatment of patients, and modern research is devoted to advancing and understanding these technologies. Ethical Implications of Reshaping Healthcare With Emerging Technologies includes the most up-to-date research in the fields of healthcare and medicine worldwide, provides answers to the forms of treatment that are already possible in medicine, and illuminates the future possibilities that are already being researched. In addition, today's knowledge is translated and shown in how new technologies such as autonomous VR-system can be used for pain reduction as part of a treatment. Finally, this book examines the ethical guidelines in healthcare and medicine that are associated with the rapid development of these technologies. This book will be useful for the healthcare industry, hospital administration, the health insurance industry, doctors, healthcare workers, business professionals, IT specialists, medical software designers, scientists, practitioners, researchers, academicians, and students looking for the latest information on the use of emerging technologies in healthcare settings.

Integrating AI in IoT Analytics on the Cloud for Healthcare Applications
Integrating AI in IoT Analytics on the Cloud for Healthcare Applications

Author: Jeya Mala, D.

Publisher: IGI Global

Published: 2022-01-07

Total Pages: 312

ISBN-13: 1799891348

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Internet of things (IoT) applications employed for healthcare generate a huge amount of data that needs to be analyzed to produce the expected reports. To accomplish this task, a cloud-based analytical solution is ideal in order to generate faster reports in comparison to the traditional way. Given the current state of the world in which every day IoT devices are developed to provide healthcare solutions, it is essential to consider the mechanisms used to collect and analyze the data to provide thorough reports. Integrating AI in IoT Analytics on the Cloud for Healthcare Applications applies artificial intelligence (AI) in edge analytics for healthcare applications, analyzes the impact of tools and techniques in edge analytics for healthcare, and discusses security solutions for edge analytics in healthcare IoT. Covering topics such as data analytics and next generation healthcare systems, it is ideal for researchers, academicians, technologists, IT specialists, data scientists, healthcare industries, IoT developers, data security analysts, educators, and students.