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This book provides a general overview of intelligence in health policy, health-care organizations and health services in the light of the current EU digital agenda, which aims to make health data and e-health tools publicly available. The first part analyses the implications of knowledge management and decision-making procedures for intelligent health policies and governance. The second part discusses in detail the concept of intelligence and illustrates why the perspective of organizational intelligence offers a solution to contemporary problems in health care, while the third part focuses on intelligent leadership models in health-care organizations. Providing a guide to new ways of understanding, developing, and reforming health policy and health services, it appeals to scholars as well as decision-makers in health governance and health-care institutions.
We are in the early stages of the next big platform shift in healthcare computing. Fueled by Artificial Intelligence (AI) and the Cloud, this shift is already transforming the way health and medical services are provided. As the industry transitions from static digital repositories to intelligent systems, there will be winners and losers in the race to innovate and automate the provision of services. Critical to success will be the role leaders play in shaping the use of AI to be less "artificial" and more "intelligent" in support of improving processes to deliver care and keep people healthy and productive across all care settings. This book defines key technical, process, people, and ethical issues that need to be understood and addressed in successfully planning and executing an enterprise-wide AI plan. It provides clinical and business leaders with a framework for moving organizations from the aspiration to execution of intelligent systems to improve clinical, operational, and financial performance.
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
This book calls on policymakers, managers, educators and clinical staff to apply and nurture intelligent kindness in the organisation and delivery of care.
Artificial Intelligence in Behavioral and Mental Health Care summarizes recent advances in artificial intelligence as it applies to mental health clinical practice. Each chapter provides a technical description of the advance, review of application in clinical practice, and empirical data on clinical efficacy. In addition, each chapter includes a discussion of practical issues in clinical settings, ethical considerations, and limitations of use. The book encompasses AI based advances in decision-making, in assessment and treatment, in providing education to clients, robot assisted task completion, and the use of AI for research and data gathering. This book will be of use to mental health practitioners interested in learning about, or incorporating AI advances into their practice and for researchers interested in a comprehensive review of these advances in one source. - Summarizes AI advances for use in mental health practice - Includes advances in AI based decision-making and consultation - Describes AI applications for assessment and treatment - Details AI advances in robots for clinical settings - Provides empirical data on clinical efficacy - Explores practical issues of use in clinical settings
This timely book addresses gaps in the understanding of how health information technology (IT) impacts on clinical workflows and how the effective implementation of these workflows are central to the safe and effective delivery of care to patients. It features clearly structured chapters covering a range of topics, including aspects of clinical workflows relevant to both practitioners and patients, tools for recording clinical workflow data techniques for potentially redesigning health IT enabled care coordination. Cognitive Informatics: Reengineering Clinical Workflow for More Efficient and Safer Care enables readers to develop a deeper understanding of clinical workflows and how these can potentially be modified to facilitate greater efficiency and safety in care provision, providing a valuable resource for both biomedical and health informatics professionals and trainees.
This book presents the papers included in the proceedings of the 5th International Conference of Reliable Information and Communication Technology 2020 (IRICT 2020) that was held virtually on December 21–22, 2020. The main theme of the book is “Innovative Systems for Intelligent Health Informatics”. A total of 140 papers were submitted to the conference, but only 111 papers were published in this book. The book presents several hot research topics which include health informatics, bioinformatics, information retrieval, artificial intelligence, soft computing, data science, big data analytics, Internet of things (IoT), intelligent communication systems, information security, information systems, and software engineering.
Many Americans believe that people who lack health insurance somehow get the care they really need. Care Without Coverage examines the real consequences for adults who lack health insurance. The study presents findings in the areas of prevention and screening, cancer, chronic illness, hospital-based care, and general health status. The committee looked at the consequences of being uninsured for people suffering from cancer, diabetes, HIV infection and AIDS, heart and kidney disease, mental illness, traumatic injuries, and heart attacks. It focused on the roughly 30 million-one in seven-working-age Americans without health insurance. This group does not include the population over 65 that is covered by Medicare or the nearly 10 million children who are uninsured in this country. The main findings of the report are that working-age Americans without health insurance are more likely to receive too little medical care and receive it too late; be sicker and die sooner; and receive poorer care when they are in the hospital, even for acute situations like a motor vehicle crash.
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.
Metaverse Applications for Intelligent Healthcare explores the exciting intersection of artificial intelligence (AI) and the metaverse in the field of healthcare. The use of AI technology in healthcare has already shown great potential in assisting with diagnosis, treatment, and patient care. The metaverse, with its immersive virtual environments, has the potential to revolutionize healthcare by making it more accessible, efficient, and personalized. This book introduces various applications of the metaverse in healthcare, including virtual consultations, remote patient monitoring, and virtual rehabilitation. The book discusses how the metaverse can be used to provide immersive experiences that empower patients and providers, while also offering unique learning opportunities. The book is ideal for researchers, practitioners, healthcare professionals, scholars, and students who are interested in exploring the cutting-edge technology of AI and the metaverse in healthcare. It offers insights into the future of healthcare, and how these technologies can be used to provide better care to patients. By combining the latest research in AI and the metaverse, this book provides a comprehensive overview of the potential applications of these technologies in healthcare.