This work surveys the state-of-the-art of information visualization systems for exploring and querying Electronic Health Record systems (EHRs). It examines how systems differ in their features and highlights how these differences are related to their design and the medical scenarios that they tackle.

This book provides innovative practical suggestions regarding the production and management of medical records that are designed to address the inconsistencies and errors that have been highlighted especially in relation to national eHealth programs. Challenges and lessons that have emerged from the use of clinical information and the design of medical records are discussed, and principles underpinning the implementation of health IT are critically examined. New trends in the use of clinical data are explored in depth, with analysis of issues relating to integration and sharing of patient information, data visualization, big data analytics, and the requirements of modern electronic health records. The spirit pervading the book is one of co-production, in which the needs of practitioners are taken into account from the outset. Readers will learn the basic concepts of how clinical information emanating from the doctor–patient relationship can be effectively integrated with genetic and environmental data and analyzed by complex algorithms with the goal of improving medical decision making and patient care. The book, written by European experts and researchers, will be of interest to all stakeholders in the field, including doctors, technicians, and policy makers.

Machine learning (ML) is the fastest growing field in computer science, and Health Informatics (HI) is amongst the greatest application challenges, providing future benefits in improved medical diagnoses, disease analyses, and pharmaceutical development. However, successful ML for HI needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization. Tackling complex challenges needs both disciplinary excellence and cross-disciplinary networking without any boundaries. Following the HCI-KDD approach, in combining the best of two worlds, it is aimed to support human intelligence with machine intelligence. This state-of-the-art survey is an output of the international HCI-KDD expert network and features 22 carefully selected and peer-reviewed chapters on hot topics in machine learning for health informatics; they discuss open problems and future challenges in order to stimulate further research and international progress in this field.

The field of health is an increasingly complex and technical one; and an area in which a more multidisciplinary approach would undoubtedly be beneficial in many ways. This book presents papers from the conference ‘Health – Exploring Complexity: An Interdisciplinary Systems Approach’, held in Munich, Germany, from August 28th to September 2nd 2016. This joint conference unites the conferences of the German Association for Medical Informatics, Biometry and Epidemiology (GMDS), the German Society for Epidemiology (DGEpi), the International Epidemiological Association - European Region, and the European Federation for Medical Informatics (EFMI). These societies already have long-standing experience of integrating the disciplines of medical informatics, biometry, epidemiology and health data management. The book contains over 160 papers, and is divided into 14 sections covering subject areas such as: health and clinical information systems; eHealth and telemedicine; big data and advanced analytics; and evidence-based health informatics, evaluation and education, among many others. The book will be of value to all those working in the field of health and interested in finding new ways to enable the collaboration of different scientific disciplines and the establishment of comprehensive methodological approaches.

This is an open access book. Time is an exceptional dimension with high relevance in medicine, engineering, business, science, biography, history, planning, or project management. Understanding time-oriented data via visual representations enables us to learn from the past in order to predict, plan, and build the future. This second edition builds upon the great success of the first edition. It maintains a brief introduction to visualization and a review of historical time-oriented visual representations. At its core, the book develops a systematic view of the visualization of time-oriented data. Separate chapters discuss interaction techniques and computational methods for supporting the visual data analysis. Many examples and figures illustrate the introduced concepts and techniques. So, what is new for the second edition? First of all, the second edition is now published as an open-access book so that anyone interested in the visualization of time and time-oriented data can read it. Second, the entire content has been revised and expanded to represent state-of-the-art knowledge. The chapter on interaction support now includes advanced methods for interacting with visual representations of time-oriented data. The second edition also covers the topics of data quality as well as segmentation and labeling. The comprehensive survey of classic and contemporary visualization techniques now provides more than 150 self-contained descriptions accompanied by illustrations and corresponding references. A completely new chapter describes how the structured survey can be used for the guided selection of suitable visualization techniques. For the second edition, our TimeViz Browser, the digital pendant to the survey of visualization techniques, received a major upgrade. It includes the same set of techniques as the book, but comes with additional filter and search facilities allowing scientists and practitioners to find exactly the solutions they are interested in.

This book (vol. 1) presents the proceedings of the IUPESM World Congress on Biomedical Engineering and Medical Physics, a triennially organized joint meeting of medical physicists, biomedical engineers and adjoining health care professionals. Besides the purely scientific and technological topics, the 2018 Congress will also focus on other aspects of professional involvement in health care, such as education and training, accreditation and certification, health technology assessment and patient safety. The IUPESM meeting is an important forum for medical physicists and biomedical engineers in medicine and healthcare learn and share knowledge, and discuss the latest research outcomes and technological advancements as well as new ideas in both medical physics and biomedical engineering field.

This textbook provides a detailed resource introducing the subdiscipline of mental health informatics. It systematically reviews the methods, paradigms, tools and knowledge base in both clinical and bioinformatics and across the spectrum from research to clinical care. Key foundational technologies, such as terminologies, ontologies and data exchange standards are presented and given context within the complex landscape of mental health conditions, research and care. The learning health system model is utilized to emphasize the bi-directional nature of the translational science associated with mental health processes. Descriptions of the data, technologies, paradigms and products that are generated by and used in each process and their limitations are discussed. Mental Health Informatics: Enabling a Learning Mental Healthcare System is a comprehensive introductory resource for students, educators and researchers in mental health informatics and related behavioral sciences. It is an ideal resource for use in a survey course for both pre- and post-doctoral training programs, as well as for healthcare administrators, funding entities, vendors and product developers working to make mental healthcare more evidence-based.