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Despite a strong commitment to delivering quality health care, persistent problems involving medical errors and ineffective treatment continue to plague the industry. Many of these problems are the consequence of poor information and technology (IT) capabilities, and most importantly, the lack cognitive IT support. Clinicians spend a great deal of time sifting through large amounts of raw data, when, ideally, IT systems would place raw data into context with current medical knowledge to provide clinicians with computer models that depict the health status of the patient. Computational Technology for Effective Health Care advocates re-balancing the portfolio of investments in health care IT to place a greater emphasis on providing cognitive support for health care providers, patients, and family caregivers; observing proven principles for success in designing and implementing IT; and accelerating research related to health care in the computer and social sciences and in health/biomedical informatics. Health care professionals, patient safety advocates, as well as IT specialists and engineers, will find this book a useful tool in preparation for crossing the health care IT chasm.
The implementation of cloud technologies in healthcare is paving the way to more effective patient care and management for medical professionals around the world. As more facilities start to integrate cloud computing into their healthcare systems, it is imperative to examine the emergent trends and innovations in the field. Cloud Computing Systems and Applications in Healthcare features innovative research on the impact that cloud technology has on patient care, disease management, and the efficiency of various medical systems. Highlighting the challenges and difficulties in implementing cloud technology into the healthcare field, this publication is a critical reference source for academicians, technology designers, engineers, professionals, analysts, and graduate students.
New technology always raises compelling ethical questions. As those in medicine increasingly depend on computers and other intelligent machines, the intersection of ethics, computing and the health professions grows much more complex and significant. This book attempts systematically to identify and address the full range of ethical issues that arise when intelligent machines are used in medicine, nursing, psychology, and allied health professions. It maps and explores a variety of important issues and controversies, including ethics and evaluation in computational medicine, patient and provider confidentiality, responsibility for use of computers in medicine, appropriate use of decision support systems, outcomes of research and computational prognosis (including mortality predictions), and computer-based biomedical research - especially meta-analysis. This book is accessible to participants in the fields of bioethics and medical informatics. It is appropriate for physicians, nurses, administrators, ethicists, health attorneys, advanced undergraduates and graduate students.
With skyrocketing costs due to the increase in the elderly population, a rapid increase in lifestyle-related and chronic diseases, demand for new medical treatments and technologies, and a shortage in the number of available clinicians, nurses, and other caregivers, the challenges facing the healthcare industry seem insurmountable. However, by tra
Important Notice: The digital edition of this book is missing some of the images or content found in the physical edition. An introductory computer literacy text for nurses and other healthcare students, Introduction to Computers for Healthcare Professionals explains hardware, popular software programs, operating systems, and computer assisted communication. The Fifth Edition of this best-selling text has been revised and now includes content on on online storage, communication and online learning including info on PDA's, iPhones, IM, and other media formats, and another chapter on distance learning including video conferencing and streaming video.
The practice of modern medicine and biomedical research requires sophisticated information technologies with which to manage patient information, plan diagnostic procedures, interpret laboratory results, and carry out investigations. Biomedical Informatics provides both a conceptual framework and a practical inspiration for this swiftly emerging scientific discipline at the intersection of computer science, decision science, information science, cognitive science, and biomedicine. Now revised and in its third edition, this text meets the growing demand by practitioners, researchers, and students for a comprehensive introduction to key topics in the field. Authored by leaders in medical informatics and extensively tested in their courses, the chapters in this volume constitute an effective textbook for students of medical informatics and its areas of application. The book is also a useful reference work for individual readers needing to understand the role that computers can play in the provision of clinical services and the pursuit of biological questions. The volume is organized so as first to explain basic concepts and then to illustrate them with specific systems and technologies.
This book focuses on the role of computers in the provision of medical services. It provides both a conceptual framework and a practical approach for the implementation and management of IT used to improve the delivery of health care. Inspired by a Stanford University training program, it fills the need for a high quality text in computers and medicine. It meets the growing demand by practitioners, researchers, and students for a comprehensive introduction to key topics in the field. Completely revised and expanded, this work includes several new chapters filled with brand new material.
Applied Computing in Medicine and Health is a comprehensive presentation of on-going investigations into current applied computing challenges and advances, with a focus on a particular class of applications, primarily artificial intelligence methods and techniques in medicine and health. Applied computing is the use of practical computer science knowledge to enable use of the latest technology and techniques in a variety of different fields ranging from business to scientific research. One of the most important and relevant areas in applied computing is the use of artificial intelligence (AI) in health and medicine. Artificial intelligence in health and medicine (AIHM) is assuming the challenge of creating and distributing tools that can support medical doctors and specialists in new endeavors. The material included covers a wide variety of interdisciplinary perspectives concerning the theory and practice of applied computing in medicine, human biology, and health care. Particular attention is given to AI-based clinical decision-making, medical knowledge engineering, knowledge-based systems in medical education and research, intelligent medical information systems, intelligent databases, intelligent devices and instruments, medical AI tools, reasoning and metareasoning in medicine, and methodological, philosophical, ethical, and intelligent medical data analysis. - Discusses applications of artificial intelligence in medical data analysis and classifications - Provides an overview of mobile health and telemedicine with specific examples and case studies - Explains how behavioral intervention technologies use smart phones to support a patient centered approach - Covers the design and implementation of medical decision support systems in clinical practice using an applied case study approach
This series is intended for the rapidly increasing number of health care professionals who have rudimentary knowledge and experience in health care computing and are seeking opportunities to expand their horizons. It does not attempt to compete with the primers already on the market. Eminent international experts will edit, author, or contribute to each volume in order to provide comprehensive and current accounts of in novations and future trends in this quickly evolving field. Each book will be practical, easy to use, and weIl referenced. Our aim is for the series to encompass all of the health professions by focusing on specific professions, such as nursing, in individual volumes. However, integrated computing systems are only one tool for improving communication among members of the health care team. Therefore, it is our hope that the series will stimulate professionals to explore additional me ans of fostering interdisciplinary exchange. This se ries springs from a professional collaboration that has grown over the years into a highly valued personal friendship. Our joint values put people first. If the Computers in Health Care series lets us share those values by helping health care professionals to communicate their ideas for the benefit of patients, then our efforts will have succeeded.
Green Computing and Predictive Analytics for Healthcare excavates the rudimentary concepts of Green Computing, Big Data and the Internet of Things along with the latest research development in the domain of healthcare. It also covers various applications and case studies in the field of computer science with state-of-the-art tools and technologies. The rapid growth of the population is a challenging issue in maintaining and monitoring various experiences of quality of service in healthcare. The coherent usage of these limited resources in connection with optimum energy consumption has been becoming more important. The major healthcare nodes are gradually becoming Internet of Things-enabled, and sensors, work data and the involvement of networking are creating smart campuses and smart houses. The book includes chapters on the Internet of Things and Big Data technologies. Features: Biomedical data monitoring under the Internet of Things Environment data sensing and analyzing Big data analytics and clustering Machine learning techniques for sudden cardiac death prediction Robust brain tissue segmentation Energy-efficient and green Internet of Things for healthcare applications Blockchain technology for the healthcare Internet of Things Advanced healthcare for domestic medical tourism system Edge computing for data analytics This book on Green Computing and Predictive Analytics for Healthcare aims to promote and facilitate the exchange of research knowledge and findings across different disciplines on the design and investigation of healthcare data analytics. It can also be used as a textbook for a master’s course in biomedical engineering. This book will also present new methods for medical data evaluation and the diagnosis of different diseases to improve quality-of-life in general and for better integration of Internet of Things into society. Dr. Sourav Banerjee is an Assistant Professor at the Department of Computer Science and Engineering of Kalyani Government Engineering College, Kalyani, West Bengal, India. His research interests include Big Data, Cloud Computing, Distributed Computing and Mobile Communications. Dr. Chinmay Chakraborty is an Assistant Professor at the Department of Electronics and Communication Engineering, Birla Institute of Technology, Mesra, India. His main research interests include the Internet of Medical Things, WBAN, Wireless Networks, Telemedicine, m-Health/e-Health and Medical Imaging. Dr. Kousik Dasgupta is an Assistant Professor at the Department of Computer Science and Engineering, Kalyani Government Engineering College, India. His research interests include Computer Vision, AI/ML, Cloud Computing, Big Data and Security.