Subject search terms: Medical informatics, nursing informatics; Keyword search terms: health care informatics, health care technology.
Advances in Informatics, Management and Technology in Healthcare by
Data science, informatics and technology have inspired health professionals and informaticians to improve healthcare for the benefit of all patients, and the field of biomedical and health informatics is one which has become increasingly important in recent years.This volume presents the papers delivered at ICIMTH 2022, the 20th International Conference on Informatics, Management, and Technology in Healthcare, held in Athens, Greece, from 1-3 July 2022. The ICIMTH Conference is an annual scientific event attended by scientists from around the world working in the field of biomedical and health informatics. This year, thanks to the improvement in the situation as regards the COVID-19 pandemic and the consequent lifting of restrictions, the conference was once again a live event, but virtual sessions by means of teleconferencing were also enabled for those unable to travel due to local restrictions. The field of biomedical and health informatics was examined from a very broad perspective, with participants presenting the research and application outcomes of informatics from cell to populations, including several technologies such as imaging, sensors, biomedical equipment, and management and organizational aspects, including legal and social issues. More than 230 submissions were received, with a total of 130 accepted as full papers and 19 as short communication and poster papers after review. As expected, a significant number of papers were related to the COVID-19 pandemic. Providing a state-of-the-art overview of biomedical and health informatics, the book will be of interest to all those working in the field of healthcare, researchers and practitioners alike
Biomedical Information Technology: Biomedical Engineering by
Biomedical Information Technology, Second Edition, contains practical, integrated clinical applications for disease detection, diagnosis, surgery, therapy and biomedical knowledge discovery, including the latest advances in the field, such as biomedical sensors, machine intelligence, artificial intelligence, deep learning in medical imaging, neural networks, natural language processing, large-scale histopathological image analysis, virtual, augmented and mixed reality, neural interfaces, and data analytics and behavioral informatics in modern medicine. The enormous growth in the field of biotechnology necessitates the utilization of information technology for the management, flow and organization of data. All biomedical professionals can benefit from a greater understanding of how data can be efficiently managed and utilized through data compression, modeling, processing, registration, visualization, communication and large-scale biological computing.
Context Sensitive Health Informatics: The Role of Informatics in Global Pandemics by
The COVID-19 pandemic has disrupted many global industries, none more so than healthcare, and has necessitated the need for health informatics innovations that can bridge time and space to provide timely care. It has also emphasized the need for a system-level informatics infrastructure to support the healthcare management of populations at a macro level, while also providing the necessary support for front line care delivery at a micro level. However, the need for change at a fast pace does not remove the need for an evidence base to support health technologies. This raises fundamental questions about how the informatics tools required can be delivered at pace without compromising the quality and safety of such tools.This book presents papers from the biennial conference on Context Sensitive Health Informatics, CSHI 2021, held as a virtual event on 15 and 16 November 2021. The theme of the 2021 conference was: The Role of Informatics in Global Pandemics, and this book includes 18 papers on a variety of topics, divided into 4 sections: health information management in the COVID-19 context; implementation of new practices and technologies in healthcare; sociotechnical analysis of task performance and workload in healthcare; and innovations in design and evaluation methods of health technologies.The book provides an overview of innovative health information systems rooted in robust scientific research on context and health information technology, and will be of interest to all those working in the field of health informatics.
Informatics and Technology in Clinical Care and Public Health by
Data, informatics, and technology are now among the most important aspects inspiring health professionals and informaticians to improve healthcare for the benefit of patients. This book presents the proceedings of the 19th annual International Conference on Informatics, Management, and Technology in Healthcare (ICIMTH 2021), held as a virtual event due to COVID-19 pandemic restrictions on 16 and 17 October 2021 in Athens, Greece. The ICIMTH conferences are a series of scientific events which bring together scientists working in the field of biomedical and health informatics from around the world. The 2021 conference examined the field of biomedical and health informatics in a very broad framework, presenting the research and application outcomes of informatics from cell to populations, and including a number of technologies such as imaging, sensors and biomedical equipment, as well as management and organizational aspects, including legal and social issues and the setting of research priorities in health informatics. A significant number of the papers included here relate to the COVID-19 pandemic.Providing an insight into the latest developments in biomedical and health informatics, the book will be of interest to all those working in the field.
Machine Learning, Big Data, and IoT for Medical Informatics by
Machine Learning, Big Data, and IoT for Medical Informatics focuses on the latest techniques adopted in the field of medical informatics. In medical informatics, machine learning, big data, and IOT-based techniques play a significant role in disease diagnosis and its prediction. In the medical field, the structure of data is equally important for accurate predictive analytics due to heterogeneity of data such as ECG data, X-ray data, and image data. Thus, this book focuses on the usability of machine learning, big data, and IOT-based techniques in handling structured and unstructured data. It also emphasizes on the privacy preservation techniques of medical data. This volume can be used as a reference book for scientists, researchers, practitioners, and academicians working in the field of intelligent medical informatics. In addition, it can also be used as a reference book for both undergraduate and graduate courses such as medical informatics, machine learning, big data, and IoT.
Measuring Capacity to Care Using Nursing Data by
Measuring Capacity to Care Using Nursing Data presents evidence-based solutions regarding the adoption of safe staffing principles and the optimum use of operational data to enable health service delivery strategies that result in improved patient and organizational outcomes. Readers will learn how to make better use of informatics to collect, share, link and process data collected operationally for the purpose of providing real-time information to decision- makers. The book discusses topics such as dynamic health care environments, health care operational inefficiencies and costly events, how to measure nursing care demand, nursing models of care, data quality and governance, and big data. The content of the book is a valuable source for graduate students in informatics, nurses, nursing managers and several members involved in health care who are interested in learning more about the beneficial use of informatics for improving their services. Presents and discusses evidences from real-world case studies from multiple countries Provides detailed insights of health system complexity in order to improve decision- making Demonstrates the link between nursing data and its use for efficient and effective healthcare service management Discusses several limitations currently experienced and their impact on health service delivery
Meta Learning with Medical Imaging and Health Informatics Applications by
Meta-Learning, or learning to learn, has become increasingly popular in recent years. Instead of building AI systems from scratch for each machine learning task, Meta-Learning constructs computational mechanisms to systematically and efficiently adapt to new tasks. The meta-learning paradigm has great potential to address deep neural networks' fundamental challenges such as intensive data requirement, computationally expensive training, and limited capacity for transfer among tasks. This book provides a concise summary of Meta-Learning theories and their diverse applications in medical imaging and health informatics. It covers the unifying theory of meta-learning and its popular variants such as model-agnostic learning, memory augmentation, prototypical networks, and learning to optimize. The book brings together thought leaders from both machine learning and health informatics fields to discuss the current state of Meta-Learning, its relevance to medical imaging and health informatics, and future directions. First book on applying Meta Learning to medical imaging Pioneers in the field as contributing authors to explain the theory and its development Has GitHub repository consisting of various code examples and documentation to help the audience to set up Meta-Learning algorithms for their applications quickly