Intelligent Healthcare

Intelligent Healthcare PDF Author: Surbhi Bhatia
Publisher: Springer Nature
ISBN: 3030670511
Category : Technology & Engineering
Languages : en
Pages : 323

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Book Description
This book fosters a scientific debate for sophisticated approaches and cognitive technologies (such as deep learning, machine learning and advanced analytics) for enhanced healthcare services in light of the tremendous scope in the future of intelligent systems for healthcare. The authors discuss the proliferation of huge data sources (e.g. genomes, electronic health records (EHRs), mobile diagnostics, and wearable devices) and breakthroughs in artificial intelligence applications, which have unlocked the doors for diagnosing and treating multitudes of rare diseases. The contributors show how the widespread adoption of intelligent health based systems could help overcome challenges, such as shortages of staff and supplies, accessibility barriers, lack of awareness on certain health issues, identification of patient needs, and early detection and diagnosis of illnesses. This book is a small yet significant step towards exploring recent advances, disseminating state-of-the-art techniques and deploying novel technologies in intelligent healthcare services and applications. Describes the advances of computing methodologies for life and medical science data; Presents applications of artificial intelligence in healthcare along with case studies and datasets; Provides an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, and clinicians.

Intelligent Healthcare

Intelligent Healthcare PDF Author: Surbhi Bhatia
Publisher: Springer Nature
ISBN: 3030670511
Category : Technology & Engineering
Languages : en
Pages : 323

Get Book Here

Book Description
This book fosters a scientific debate for sophisticated approaches and cognitive technologies (such as deep learning, machine learning and advanced analytics) for enhanced healthcare services in light of the tremendous scope in the future of intelligent systems for healthcare. The authors discuss the proliferation of huge data sources (e.g. genomes, electronic health records (EHRs), mobile diagnostics, and wearable devices) and breakthroughs in artificial intelligence applications, which have unlocked the doors for diagnosing and treating multitudes of rare diseases. The contributors show how the widespread adoption of intelligent health based systems could help overcome challenges, such as shortages of staff and supplies, accessibility barriers, lack of awareness on certain health issues, identification of patient needs, and early detection and diagnosis of illnesses. This book is a small yet significant step towards exploring recent advances, disseminating state-of-the-art techniques and deploying novel technologies in intelligent healthcare services and applications. Describes the advances of computing methodologies for life and medical science data; Presents applications of artificial intelligence in healthcare along with case studies and datasets; Provides an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, and clinicians.

Emerging Artificial Intelligence Applications in Computer Engineering

Emerging Artificial Intelligence Applications in Computer Engineering PDF Author: Ilias G. Maglogiannis
Publisher: IOS Press
ISBN: 1586037803
Category : Computers
Languages : en
Pages : 420

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Book Description
Provides insights on how computer engineers can implement artificial intelligence (AI) in real world applications. This book presents practical applications of AI.

Smart Systems for Industrial Applications

Smart Systems for Industrial Applications PDF Author: C. Venkatesh
Publisher: John Wiley & Sons
ISBN: 1119762049
Category : Computers
Languages : en
Pages : 311

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Book Description
SMART SYSTEMS FOR INDUSTRIAL APPLICATIONS The prime objective of this book is to provide an insight into the role and advancements of artificial intelligence in electrical systems and future challenges. The book covers a broad range of topics about AI from a multidisciplinary point of view, starting with its history and continuing on to theories about artificial vs. human intelligence, concepts, and regulations concerning AI, human-machine distribution of power and control, delegation of decisions, the social and economic impact of AI, etc. The prominent role that AI plays in society by connecting people through technologies is highlighted in this book. It also covers key aspects of various AI applications in electrical systems in order to enable growth in electrical engineering. The impact that AI has on social and economic factors is also examined from various perspectives. Moreover, many intriguing aspects of AI techniques in different domains are covered such as e-learning, healthcare, smart grid, virtual assistance, etc. Audience The book will be of interest to researchers and postgraduate students in artificial intelligence, electrical and electronic engineering, as well as those engineers working in the application areas such as healthcare, energy systems, education, and others.

eHealth

eHealth PDF Author: Thomas F. Heston
Publisher: BoD – Books on Demand
ISBN: 1789235227
Category : Health & Fitness
Languages : en
Pages : 186

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Book Description
eHealth has revolutionized health care and the practice of medicine. Internet technologies have given the most rural communities access to healthcare services, and automated computer algorithms are improving medical diagnoses and speeding up the delivery of care. Handheld apps, wearable devices, and artificial intelligence lead the way, creating a global healthcare solution that is smarter and more accessible. Read what leaders in the field are doing to advance the use of electronic technology to improve global health.

Artificial Intelligence for COVID-19

Artificial Intelligence for COVID-19 PDF Author: Diego Oliva
Publisher: Springer Nature
ISBN: 3030697444
Category : Technology & Engineering
Languages : en
Pages : 594

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Book Description
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 in Healthcare

Artificial Intelligence in Healthcare PDF Author: Adam Bohr
Publisher: Academic Press
ISBN: 0128184396
Category : Computers
Languages : en
Pages : 385

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Book Description
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

AI in eHealth

AI in eHealth PDF Author: Marcelo Corrales Compagnucci
Publisher: Cambridge University Press
ISBN: 1108924859
Category : Law
Languages : en
Pages : 493

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Book Description
The emergence of digital platforms and the new application economy are transforming healthcare and creating new opportunities and risks for all stakeholders in the medical ecosystem. Many of these developments rely heavily on data and AI algorithms to prevent, diagnose, treat, and monitor diseases and other health conditions. A broad range of medical, ethical and legal knowledge is now required to navigate this highly complex and fast-changing space. This collection brings together scholars from medicine and law, but also ethics, management, philosophy, and computer science, to examine current and future technological, policy and regulatory issues. In particular, the book addresses the challenge of integrating data protection and privacy concerns into the design of emerging healthcare products and services. With a number of comparative case studies, the book offers a high-level, global, and interdisciplinary perspective on the normative and policy dilemmas raised by the proliferation of information technologies in a healthcare context.

Artificial Intelligence in Medical Imaging

Artificial Intelligence in Medical Imaging PDF Author: Erik R. Ranschaert
Publisher: Springer
ISBN: 3319948784
Category : Medical
Languages : en
Pages : 369

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Book Description
This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.

Demystifying Big Data and Machine Learning for Healthcare

Demystifying Big Data and Machine Learning for Healthcare PDF Author: Prashant Natarajan
Publisher: CRC Press
ISBN: 1315389304
Category : Medical
Languages : en
Pages : 227

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Book Description
Healthcare transformation requires us to continually look at new and better ways to manage insights – both within and outside the organization today. Increasingly, the ability to glean and operationalize new insights efficiently as a byproduct of an organization’s day-to-day operations is becoming vital to hospitals and health systems ability to survive and prosper. One of the long-standing challenges in healthcare informatics has been the ability to deal with the sheer variety and volume of disparate healthcare data and the increasing need to derive veracity and value out of it. Demystifying Big Data and Machine Learning for Healthcare investigates how healthcare organizations can leverage this tapestry of big data to discover new business value, use cases, and knowledge as well as how big data can be woven into pre-existing business intelligence and analytics efforts. This book focuses on teaching you how to: Develop skills needed to identify and demolish big-data myths Become an expert in separating hype from reality Understand the V’s that matter in healthcare and why Harmonize the 4 C’s across little and big data Choose data fi delity over data quality Learn how to apply the NRF Framework Master applied machine learning for healthcare Conduct a guided tour of learning algorithms Recognize and be prepared for the future of artificial intelligence in healthcare via best practices, feedback loops, and contextually intelligent agents (CIAs) The variety of data in healthcare spans multiple business workflows, formats (structured, un-, and semi-structured), integration at point of care/need, and integration with existing knowledge. In order to deal with these realities, the authors propose new approaches to creating a knowledge-driven learning organization-based on new and existing strategies, methods and technologies. This book will address the long-standing challenges in healthcare informatics and provide pragmatic recommendations on how to deal with them.

eHealth Research, Theory and Development

eHealth Research, Theory and Development PDF Author: Hanneke Kip
Publisher: Routledge
ISBN: 1315385880
Category : Psychology
Languages : en
Pages : 412

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Book Description
This is the first book to provide a comprehensive overview of the social and technological context from which eHealth applications have arisen, the psychological principles on which they are based, and the key development and evaluation issues relevant to their successful intervention. Integrating how eHealth applications can be used for both mental and physical health issues, it presents a complete guide to what eHealth means in theory, as well as how it can be used in practice. Inspired by the principles and structure of the CeHRes Roadmap, a multidisciplinary framework that combines and uses aspects from approaches such as human-centred design, persuasive technology and business modelling, the book first examines the theoretical foundations of eHealth and then assesses its practical application and assessment. Including case studies, a glossary of key terms, and end of chapter summaries, this ground-breaking book provides a holistic overview of one of the most important recent developments in healthcare. It will be essential reading for students, researchers and professionals across the fields of health psychology, public health and design technology.