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

Developments in Healthcare Information Systems and Technologies: Models and Methods presents the latest research in healthcare information systems design, development, and deployment, benefiting researchers, practitioners, and students. Contributions investigate topics such as clinical education, electronic medical records, clinical decision support systems, and IT adoption in healthcare.

"This reference set provides a complete understanding of the development of applications and concepts in clinical, patient, and hospital information systems"--Provided by publisher.

Previously published as Strategic Information Management in Hospitals; An Introduction to Hospital Information Systems, Health Information Systems Architectures and Strategies is a definitive volume written by four authoritative voices in medical informatics. Illustrating the importance of hospital information management in delivering high quality health care at the lowest possible cost, this book provides the essential resources needed by the medical informatics specialist to understand and successfully manage the complex nature of hospital information systems. Author of the first edition's Foreword, Reed M. Gardner, PhD, Professor and Chair, Department of Medical Informatics, University of Utah and LDS Hospital, Salt Lake City, Utah, applauded the text's focus on the underlying administrative systems that are in place in hospitals throughout the world. He wrote, "These challenging systems that acquire, process and manage the patient's clinical information. Hospital information systems provide a major part of the information needed by those paying for health care." their components; health information systems; architectures of hospital information systems; and organizational structures for information management.

This book provides a practical guide to the design and implementation of health information systems in developing countries. Noting that most existing systems fail to deliver timely, reliable, and relevant information, the book responds to the urgent need to restructure systems and make them work as both a resource for routine decisions and a powerful tool for improving health services. With this need in mind, the authors draw on their extensive personal experiences to map out strategies, pinpoint common pitfalls, and guide readers through a host of conceptual and technical options. Information needs at all levels - from patient care to management of the national health system - are considered in this comprehensive guide. Recommended lines of action are specific to conditions seen in government-managed health systems in the developing world. In view of common constraints on time and resources, the book concentrates on strategies that do not require large resources, highly trained staff, or complex equipment. Throughout the book, case studies and numerous practical examples are used to explore problems and illustrate solutions. Details range from a list of weaknesses that plague most existing systems, through advice on when to introduce computers and how to choose appropriate software and hardware, to the hotly debated question of whether patient records should be kept by the patient or filed at the health unit. The book has fourteen chapters presented in four parts. Chapters in the first part, on information for decision-making, explain the potential role of health information as a managerial tool, consider the reasons why this potential is rarely realized, and propose general approaches for reform which have proved successful in several developing countries. Presentation of a six-step procedure for restructuring information systems, closely linked to an organizational model of health services, is followed by a practical discussion of the decision-making process. Reasons for the failure of most health information to influence decisions are also critically assessed. Against this background, the second and most extensive part provides a step-by-step guide to the restructuring of information systems aimed at improving the quality and relevance of data and ensuring their better use in planning and management. Steps covered include the identification of information needs and indicators, assessment of the existing system, and the collection of both routine and non-routine data using recommended procedures and instruments. Chapters also offer advice on procedures for data transmission and processing, and discuss the requirements of systems designed to collect population-based community information. Resource needs and technical tools are addressed in part three. A comprehensive overview of the resource base - from staff and training to the purchase and maintenance of equipment - is followed by chapters offering advice on the introduction of computerized systems in developing countries, and explaining the many applications of geographic information systems. Practical advice on how to restructure a health information system is provided in the final part, which considers how different interest groups can influence the design and implementation of a new system, and proposes various design options for overcoming specific problems. Experiences from several developing countries are used to illustrate strategies and designs in terms of those almost certain to fail and those that have the greatest chances of success

Modern technology has impacted healthcare and interactions between patients and healthcare providers through a variety of means including the internet, social media, mobile devices, and the internet of things. These new technologies have empowered, frustrated, educated, and confused patients by making educational materials more widely available and allowing patients to monitor their own vital signs and self-diagnose. Further analysis of these and future technologies is needed in order to provide new approaches to empowerment, reduce mistakes, and improve overall healthcare. Impacts of Information Technology on Patient Care and Empowerment is a critical scholarly resource that delves into patient access to information and the effect that access has on their relationship with healthcare providers and their health outcomes. Featuring a range of topics such as gamification, mobile computing, and risk analysis, this book is ideal for healthcare practitioners, doctors, nurses, surgeons, hospital staff, medical administrators, patient advocates, researchers, academicians, policymakers, and healthcare students.

This open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources. Developing countries are uniquely prone to large-scale emerging infectious disease outbreaks due to disruption of ecosystems, civil unrest, and poor healthcare infrastructure – and without comprehensive surveillance, delays in outbreak identification, resource deployment, and case management can be catastrophic. In combination with context-informed analytics, students will learn how non-traditional digital disease data sources – including news media, social media, Google Trends, and Google Street View – can fill critical knowledge gaps and help inform on-the-ground decision-making when formal surveillance systems are insufficient.