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.

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 book presents an internationally comprehensive perspective into the field of complex systems. It explores the challenges of and approaches to complexity from a broad range of disciplines, including big data, health care, medicine, mathematics, mechanical and systems engineering, air traffic control and finance. The book’s interdisciplinary character allows readers to identify transferable and mutually exclusive lessons learned among these disciplines and beyond. As such, it is well suited to the transfer of applications and methodologies between ostensibly incompatible disciplines. This book provides fresh perspectives on comparable issues of complexity from the top minds on systems thinking.

This book provides an important contribution to the new and growing field of 'narrative-based medicine'. It specifically addresses the largest area of medical activity primary care. It provides both a theoretical framework and practical skills for dealing with individual consultations family work clinical supervision and teamwork and offers a comprehensive approach to the whole range of work in primary care. Using a wide range of clinical examples it shows how professionals in primary care can help clarify patients' existing stories and elucidate new stories. It can be used as a training resource and includes exercises and summaries of key points to consider. It is based on and describes an established evaluated training method and is of immediate and significant practical use to readers. It is essential reading for general practitioners practice nurses and others in the primary care team psychologists family therapists counsellors and other professionals attached to primary care. GP trainers tutors and course organisers will find it a valuable educational tool. Professionals elsewhere in primary care such as pharmacists dentists and optometrists and academics in medical sociology and medical anthropology will also find it very useful.

Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.