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Danger of health misinformation online, long a concern of medical and public health professionals, has come to the forefront of societal concerns during the COVID-19 pandemic. Regardless of their motives, creators and sharers of misinformation promote non-evidence-based health advice and treatment recommendations, and often deny health methods, measures, and approaches that are supported by the best evidence of the time. Unfortunately, many infrastructural, social, and cognitive factors make individuals vulnerable to misinformation. This book aims to assist information and health professionals and educators with all phases of information provision and support, from understanding users’ inf...
The publication seeks to establish how information professionals are providing information services in in a sustainable society in an era of information disorder. It also provides the strategic direction to strengthen the global voice of libraries, inspiring and enhancing professional practice as well as enhancing international cooperation and collaboration among LIS educators and practitioners. The contents is divided according to the following key sub-themes that resonate with the title as outlined below: Library and information services in the information age Data and records in an era of information disorder Archives, data curation and preservation in the digital era Data science, analyt...
Pandemics have quickly become one of the most important subjects of the twenty-first century. This edited volume provides a comparative analysis of the ways in which pandemics are theorized and studied across several disciplines. A Multidisciplinary Approach to Pandemics has two objectives: first, to explore the growing diversity of theories and paradigms developed to study pandemics; and second, to initiate a multidisciplinary dialogue about the ontological, epistemological, paradigmatic, and normative aspects of studying pandemics across disciplines. The study of pandemics is not new. Yet despite the volume of research interest in a host of academic fields, scholars rarely talk across the disciplines. This study seeks to fill that gap by attempting to bridge disciplinary canyons. Eager to encourage this arena of conversation, this book brings together in a single volume essays by political scientists, environmental scholars, legal scholars, clinical pharmacists, economists, scholars of urban planning, scholars in health and medicine schools, and researchers in business and management.
Was nützt Künstliche Intelligenz im Gesundheitswesen, wenn diese nicht verantwortungsvoll entwickelt und genutzt wird? Das vorliegende Buch beschäftigt sich mit den grundlegenden Modellen und aktuellen Entwicklungen im Bereich der Künstlichen Intelligenz im Gesundheitswesen, diskutiert konkrete Anwendungsszenarien und stellt die enge Verbindung mit ethischen Fragestellungen her. In kompakter und verständlicher Form wird dies von ausgewiesenen Expert:innen aus unterschiedlichen Teilbereichen und Thematiken präsentiert.
Patient-centered, high-quality health care relies on the well-being, health, and safety of health care clinicians. However, alarmingly high rates of clinician burnout in the United States are detrimental to the quality of care being provided, harmful to individuals in the workforce, and costly. It is important to take a systemic approach to address burnout that focuses on the structure, organization, and culture of health care. Taking Action Against Clinician Burnout: A Systems Approach to Professional Well-Being builds upon two groundbreaking reports from the past twenty years, To Err Is Human: Building a Safer Health System and Crossing the Quality Chasm: A New Health System for the 21st Century, which both called attention to the issues around patient safety and quality of care. This report explores the extent, consequences, and contributing factors of clinician burnout and provides a framework for a systems approach to clinician burnout and professional well-being, a research agenda to advance clinician well-being, and recommendations for the field.
This monograph uses the Julia language to guide the reader through an exploration of the fundamental concepts of probability and statistics, all with a view of mastering machine learning, data science, and artificial intelligence. The text does not require any prior statistical knowledge and only assumes a basic understanding of programming and mathematical notation. It is accessible to practitioners and researchers in data science, machine learning, bio-statistics, finance, or engineering who may wish to solidify their knowledge of probability and statistics. The book progresses through ten independent chapters starting with an introduction of Julia, and moving through basic probability, di...