Visualizing Household Health

In 1256, the countess of Provence, Beatrice of Savoy, enlisted her personal physician to create a health handbook to share with her daughters. Written in French and known as the Régime du corps, this health guide would become popular and influential, with nearly seventy surviving copies made over the next two hundred years and translations in at least four other languages. In Visualizing Household Health, art historian Jennifer Borland uses the Régime to show how gender and health care converged within the medieval household. Visualizing Household Health explores the nature of the households portrayed in the Régime and how their members interacted with professionalized medicine. Borland focuses on several illustrated versions of the manuscript that contain historiated initials depicting simple scenes related to health care, such as patients’ consultations with physicians, procedures like bloodletting, and foods and beverages recommended for good health. Borland argues that these images provide important details about the nature of women’s agency in the home—and offer highly compelling evidence that women enacted multiple types of health care. Additionally, she contends, the Régime opens a window onto the history of medieval women as owners, patrons, and readers of books. Interdisciplinary in scope, this book broadens notions of the medieval medical community and the role of women in medieval health care. It will be welcomed by scholars and students of women’s history, art history, book history, and the history of medicine.

"Examines several illustrated copies of the late medieval health guide known as the Régime du corps, demonstrating how the manuscripts' depictions of household care highlight female-dominated expertise within the domestic sphere"--

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.

Visualizing Health Care Statistics: A Data-Mining Approach is an introductory statistics text that demonstrates how to visualize health care statistics using Microsoft Excel and R-Project (open source statistical software) and hands-on examples using real-world data. In each chapter, students are encouraged to apply statistical knowledge to real-world health care situations. Through this approach, students develop data gathering and analysis skills all while preparing for the national Registered Health Information Technician (RHIT) exam.

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.

The comprehensive guide to imagery therapy for: the common cold, bone fractures, arthritis, hypertension, headaches, asthma, infertility, depression, pms, anxiety, obesity, and much more For years it has been widely known that the mind exerts a tremendous influence on our physical well-being—often determining the difference between health and disease. In Healing Visualizations, Dr. Gerald Epstein, a psychiatrist and pioneer in waking dream therapy, provides a new vision of how the mind can help heal the body through the power of “imaginal medicine.” Developed over fifteen years of clinical practice, Dr. Epstein’s safe, potent techniques for tapping the mind’s healing energy enable us to influence our own health with remarkably fast, positive results. More than seventy-five exercises cover specific health problems form common ailments such as allergies, colds, backaches, headaches, and arthritis to life-threatening illnesses such as heart disease and cancer. Each exercise takes just one to five minutes. And there are special visualizations for overall wellness that you can personalize to fit your own daily health and fitness needs. A revolutionary and inspiring program, Healing Visualizations is a major contribution to understanding, restoring, and maintaining the healthful unity of body and mind.

Visualizing with Text uncovers the rich palette of text elements usable in visualizations from simple labels through to documents. Using a multidisciplinary research effort spanning across fields including visualization, typography, and cartography, it builds a solid foundation for the design space of text in visualization. The book illustrates many new kinds of visualizations, including microtext lines, skim formatting, and typographic sets that solve some of the shortcomings of well-known visualization techniques. Key features: More than 240 illustrations to aid inspiration of new visualizations Eight new approaches to data visualization leveraging text Quick reference guide for visualization with text Builds a solid foundation extending current visualization theory Bridges between visualization, typography, text analytics, and natural language processing The author website, including teaching exercises and interactive demos and code, can be found here. Designers, developers, and academics can use this book as a reference and inspiration for new approaches to visualization in any application that uses text.

Geospatial health data are essential to inform public health and policy. These data can be used to quantify disease burden, understand geographic and temporal patterns, identify risk factors, and measure inequalities. Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny describes spatial and spatio-temporal statistical methods and visualization techniques to analyze georeferenced health data in R. The book covers the following topics: Manipulate and transform point, areal, and raster data, Bayesian hierarchical models for disease mapping using areal and geostatistical data, Fit and interpret spatial and spatio-temporal models with the Integrated Nested Laplace Approximations (INLA) and the Stochastic Partial Differential Equation (SPDE) approaches, Create interactive and static visualizations such as disease maps and time plots, Reproducible R Markdown reports, interactive dashboards, and Shiny web applications that facilitate the communication of insights to collaborators and policy makers. The book features fully reproducible examples of several disease and environmental applications using real-world data such as malaria in The Gambia, cancer in Scotland and USA, and air pollution in Spain. Examples in the book focus on health applications, but the approaches covered are also applicable to other fields that use georeferenced data including epidemiology, ecology, demography or criminology. The book provides clear descriptions of the R code for data importing, manipulation, modeling and visualization, as well as the interpretation of the results. This ensures contents are fully reproducible and accessible for students, researchers and practitioners.