Visualizing Disease

Visual anatomy books have been a staple of medical practice and study since the mid-sixteenth century. But the visual representation of diseased states followed a very different pattern from anatomy, one we are only now beginning to investigate and understand. With Visualizing Disease, Domenico Bertoloni Meli explores key questions in this domain, opening a new field of inquiry based on the analysis of a rich body of arresting and intellectually challenging images reproduced here both in black and white and in color. Starting in the Renaissance, Bertoloni Meli delves into the wide range of figures involved in the early study and representation of disease, including not just men of medicine, like anatomists, physicians, surgeons, and pathologists, but also draftsmen and engravers. Pathological preparations proved difficult to preserve and represent, and as Bertoloni Meli takes us through a number of different cases from the Renaissance to the mid-nineteenth century, we gain a new understanding of how knowledge of disease, interactions among medical men and artists, and changes in the technologies of preservation and representation of specimens interacted to slowly bring illustration into the medical world.

Researchers have used a variety of techniques over the past century to gain fun- mental insights in the field of immunology and, as technology has advanced, so too has the ability of researchers to delve deeper into the biological mechanics of immunity. The immune system is exceedingly complex and must patrol the entire body to protect us from foreign invaders. This requires the immune system to be highly mobile and adaptable - able to respond to diverse microbial challenges while maintaining the ability to distinguish self from a foreign invader. This latter feature is of great importance because the immune system is equipped with toxic mediators, and a failure in self/non-self discrimination can result in serious diseases. Fortunately, in most cases, the immune system operates within the framework of its elegant design and protects us from diverse microbial challenges without initiating disease. Because the immune system is not confined to a single tissue, a comprehensive understanding of immunity requires that research be conducted at the molecular, cellular, and systems level. Immune cells often find customized solutions to h- dling microbial insults that depend on the tissue(s) in which the pathogen is found.

Visualizing Microbiology, 1st Edition provides an introduction to microbiology for students who require the basic fundamentals of microbiology as a requirement for their major or course of study. The unique visual pedagogy of the Visualizing series provides a powerful combination of content, visuals, multimedia and videos ideal for microbiology. A dynamic learning platform encouraging engagement with real clinical content, Visualizing Microbiology also brings the narrative to life with integrated multimedia helping students see and understand the unseen in the world of microbiology.

Computer-based infectious disease surveillance systems are capable of real-time or near real-time detection of serious illnesses and potential bioterrorism agent exposures and represent a major step forward in disease surveillance. Infectious Disease Informatics: Syndromic Surveillance for Public Health and Bio-Defense is an in-depth monograph that analyzes and evaluates the outbreak modeling and detection capabilities of existing surveillance systems under a unified framework, and presents the first book-length coverage of the subject from an informatics-driven perspective. Individual chapters consider the state of the art, including the facilitation of data collection, sharing and transmission; a focus on various outbreak detection methods; data visualization and information dissemination issues; and system assessment and other policy issues. Eight chapters then report on several real-world case studies, summarizing and comparing eight syndromic surveillance systems, including those that have been adopted by many public health agencies (e.g., RODS and BioSense). The book concludes with a discussion of critical issues and challenges, with a look to future directions. This book is an excellent source of current information for researchers in public health and IT. Government public health officials and private-sector practitioners in both public health and IT will find the most up-to-date information available, and students from a variety of disciplines, including public health, biostatistics, information systems, computer science, and public administration and policy will get a comprehensive look at the concepts, techniques, and practices of syndromic surveillance.

This book provides a practically orientated resource that details the use a range of imaging techniques across major specialties plus those that are less well represented in standard textbooks (e.g. cardiothoracic surgery, palliative care, geriatric medicine, skin conditions from diverse ethnic groups). Emphasis is placed on enabling the reader to interpret images and clinical data, while avoiding mistakes and pitfalls in their day-to-day practice. Detailed question and answer sections along with insightful videos reinforce key messages (e.g. visualizing heart murmurs). Grading of questions aids navigation, with more difficult questions to benefit the high-flying students/junior doctors preparing for postgraduate exams/physician associates and advanced nurse practitioners working in a specialist area. Practical Guide to Visualizing Medicine: A Self-Assessment Manual concisely covers how to use imaging techniques in medicine, surgery, pediatrics, obstetrics and gynecology. It emphasizes the value of being able to accurately visualize signs and symptoms to make accurate diagnoses and provide patient-centered care. The added insight given from experienced medical educators on how to select an appropriate medical specialty makes this work critical for all trainee and early-career medical practitioners and allied healthcare professionals.

The only data visualization book written by and for health and healthcare professionals. In health and healthcare, data and information are coming at organizations faster than they can consume and interpret it. Health providers, payers, public health departments, researchers, and health information technology groups know the ability to analyze and communicate this vast array of data in a clear and compelling manner is paramount to success. However, they simply cannot find experienced people with the necessary qualifications. The quickest (and often the only) route to meeting this challenge is to hire smart people and train them. Visualizing Health and Healthcare Data: Creating Clear and Compelling Visualizations to "See how You're Doing" is a one-of-a-kind book for health and healthcare professionals to learn the best practices of data visualization specific to their field. It provides a high-level summary of health and healthcare data, an overview of relevant visual intelligence research, strategies and techniques to gather requirements, and how to build strong teams with the expertise required to create dashboards and reports that people love to use. Clear and detailed explanations of data visualization best practices will help you understand the how and the why. Learn how to build beautiful and useful data products that deliver powerful insights for the end user Follow along with examples of data visualization best practices, including table and graph design for health and healthcare data Learn the difference between dashboards, reports, multidimensional exploratory displays and infographics (and why it matters) Avoid common mistakes in data visualization by learning why they do not work and better ways to display the data Written by a top leader in the field of health and healthcare data visualization, this book is an excellent resource for top management in healthcare, as well as entry-level to experienced data analysts in any health-related organization.

A human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems. One of the original goals of artificial intelligence research was to endow intelligent agents with human-level natural language capabilities. Recent AI research, however, has focused on applying statistical and machine learning approaches to big data rather than attempting to model what people do and how they do it. In this book, Marjorie McShane and Sergei Nirenburg return to the original goal of recreating human-level intelligence in a machine. They present a human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems that emphasizes meaning--the deep, context-sensitive meaning that a person derives from spoken or written language.