Visualizing Health Care Statistics A Data Mining Approach
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| Author | : Zada T. Wicker |
| Publisher | : Jones & Bartlett Learning |
| Total Pages | : 268 |
| Release | : 2020-09-25 |
| Genre | : Business & Economics |
| ISBN | : 1284226743 |
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.
| Author | : J. Burton Browning |
| Publisher | : Lulu.com |
| Total Pages | : 542 |
| Release | : |
| Genre | : |
| ISBN | : 1365854167 |
| Author | : William S. Cleveland |
| Publisher | : Hobart Press |
| Total Pages | : 378 |
| Release | : 1993 |
| Genre | : Computers |
| ISBN | : |
| Author | : Farrokh Alemi |
| Publisher | : |
| Total Pages | : 553 |
| Release | : 2019 |
| Genre | : Data mining |
| ISBN | : 9781640550636 |
Big Data in Healthcare: Statistical Analysis of the Electronic Health Record provides the statistical tools that healthcare leaders need to organize and interpret their data. Designed for accessibility to those with a limited mathematics background, the book demonstrates how to leverage EHR data for applications as diverse as healthcare marketing, pay for performance, cost accounting, and strategic management. Topics include:* Using real-world data to compare hospitals' performance. * Measuring the prognosis of patients through massive data* Distinguishing between fake claims and true improvements* Comparing the effectiveness of different interventions using causal analysis* Benchmarking different clinicians on the same set of patients* Remove confounding in observational dataThis book can be used in introductory courses on hypothesis testing, intermediate courses on regression, and advanced courses on causal analysis. It can also be used to learn SQL language. Its extensive online instructor resources include course syllabi, PowerPoint and video lectures, Excel exercises, individual and team assignments, answers to assignments, and student-organized tutorials. Big Data in Healthcare applies the building blocks of statistical thinking to the basic challenges that healthcare leaders face every day. Prepare for those challenges with the clear understanding of your data that statistical analysis can bring--and make the best possible decisions for maximum performance in the competitive field of healthcare.
| Author | : H. Dan O'Hair |
| Publisher | : John Wiley & Sons |
| Total Pages | : 1043 |
| Release | : 2020-04-24 |
| Genre | : Language Arts & Disciplines |
| ISBN | : 1119399874 |
An authoritative survey of different contexts, methodologies, and theories of applied communication The field of Applied Communication Research (ACR) has made substantial progress over the past five decades in studying communication problems, and in making contributions to help solve them. Changes in society, human relationships, climate and the environment, and digital media have presented myriad contexts in which to apply communication theory. The Handbook of Applied Communication Research addresses a wide array of contemporary communication issues, their research implications in various contexts, and the challenges and opportunities for using communication to manage problems. This innovative work brings together the diverse perspectives of a team of notable international scholars from across disciplines. The Handbook of Applied Communication Research includes discussion and analysis spread across two comprehensive volumes. Volume one introduces ACR, explores what is possible in the field, and examines theoretical perspectives, organizational communication, risk and crisis communication, and media, data, design, and technology. The second volume focuses on real-world communication topics such as health and education communication, legal, ethical, and policy issues, and volunteerism, social justice, and communication activism. Each chapter addresses a specific issue or concern, and discusses the choices faced by participants in the communication process. This important contribution to communication research: Explores how various communication contexts are best approached Addresses balancing scientific findings with social and cultural issues Discusses how and to what extent media can mitigate the effects of adverse events Features original findings from ongoing research programs and original communication models and frameworks Presents the best available research and insights on where current research and best practices should move in the future A major addition to the body of knowledge in the field, The Handbook of Applied Communication Research is an invaluable work for advanced undergraduate students, graduate students, and scholars.
| Author | : Michael Friendly |
| Publisher | : CRC Press |
| Total Pages | : 700 |
| Release | : 2015-12-16 |
| Genre | : Mathematics |
| ISBN | : 1498725864 |
An Applied Treatment of Modern Graphical Methods for Analyzing Categorical DataDiscrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data presents an applied treatment of modern methods for the analysis of categorical data, both discrete response data and frequency data. It explains how to use graphical meth
| Author | : Nadieh Bremer |
| Publisher | : CRC Press |
| Total Pages | : 429 |
| Release | : 2021-02-09 |
| Genre | : Computers |
| ISBN | : 0429816820 |
In Data Sketches, Nadieh Bremer and Shirley Wu document the deeply creative process behind 24 unique data visualization projects, and they combine this with powerful technical insights which reveal the mindset behind coding creatively. Exploring 12 different themes – from the Olympics to Presidents & Royals and from Movies to Myths & Legends – each pair of visualizations explores different technologies and forms, blurring the boundary between visualization as an exploratory tool and an artform in its own right. This beautiful book provides an intimate, behind-the-scenes account of all 24 projects and shares the authors’ personal notes and drafts every step of the way. The book features: Detailed information on data gathering, sketching, and coding data visualizations for the web, with screenshots of works-in-progress and reproductions from the authors’ notebooks Never-before-published technical write-ups, with beginner-friendly explanations of core data visualization concepts Practical lessons based on the data and design challenges overcome during each project Full-color pages, showcasing all 24 final data visualizations This book is perfect for anyone interested or working in data visualization and information design, and especially those who want to take their work to the next level and are inspired by unique and compelling data-driven storytelling.
| Author | : L. Ohno-Machado |
| Publisher | : IOS Press |
| Total Pages | : 2078 |
| Release | : 2019-11-12 |
| Genre | : Medical |
| ISBN | : 164368003X |
Combining and integrating cross-institutional data remains a challenge for both researchers and those involved in patient care. Patient-generated data can contribute precious information to healthcare professionals by enabling monitoring under normal life conditions and also helping patients play a more active role in their own care. This book presents the proceedings of MEDINFO 2019, the 17th World Congress on Medical and Health Informatics, held in Lyon, France, from 25 to 30 August 2019. The theme of this year’s conference was ‘Health and Wellbeing: E-Networks for All’, stressing the increasing importance of networks in healthcare on the one hand, and the patient-centered perspective on the other. Over 1100 manuscripts were submitted to the conference and, after a thorough review process by at least three reviewers and assessment by a scientific program committee member, 285 papers and 296 posters were accepted, together with 47 podium abstracts, 7 demonstrations, 45 panels, 21 workshops and 9 tutorials. All accepted paper and poster contributions are included in these proceedings. The papers are grouped under four thematic tracks: interpreting health and biomedical data, supporting care delivery, enabling precision medicine and public health, and the human element in medical informatics. The posters are divided into the same four groups. The book presents an overview of state-of-the-art informatics projects from multiple regions of the world; it will be of interest to anyone working in the field of medical informatics.
| Author | : Yanchang Zhao |
| Publisher | : Academic Press |
| Total Pages | : 251 |
| Release | : 2012-12-31 |
| Genre | : Mathematics |
| ISBN | : 012397271X |
R and Data Mining introduces researchers, post-graduate students, and analysts to data mining using R, a free software environment for statistical computing and graphics. The book provides practical methods for using R in applications from academia to industry to extract knowledge from vast amounts of data. Readers will find this book a valuable guide to the use of R in tasks such as classification and prediction, clustering, outlier detection, association rules, sequence analysis, text mining, social network analysis, sentiment analysis, and more.Data mining techniques are growing in popularity in a broad range of areas, from banking to insurance, retail, telecom, medicine, research, and government. This book focuses on the modeling phase of the data mining process, also addressing data exploration and model evaluation.With three in-depth case studies, a quick reference guide, bibliography, and links to a wealth of online resources, R and Data Mining is a valuable, practical guide to a powerful method of analysis. - Presents an introduction into using R for data mining applications, covering most popular data mining techniques - Provides code examples and data so that readers can easily learn the techniques - Features case studies in real-world applications to help readers apply the techniques in their work
| Author | : Ian H. Witten |
| Publisher | : Elsevier |
| Total Pages | : 665 |
| Release | : 2011-02-03 |
| Genre | : Computers |
| ISBN | : 0080890369 |
Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including new material on Data Transformations, Ensemble Learning, Massive Data Sets, Multi-instance Learning, plus a new version of the popular Weka machine learning software developed by the authors. Witten, Frank, and Hall include both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. The book is targeted at information systems practitioners, programmers, consultants, developers, information technology managers, specification writers, data analysts, data modelers, database R&D professionals, data warehouse engineers, data mining professionals. The book will also be useful for professors and students of upper-level undergraduate and graduate-level data mining and machine learning courses who want to incorporate data mining as part of their data management knowledge base and expertise. - Provides a thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques to your data mining projects - Offers concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods - Includes downloadable Weka software toolkit, a collection of machine learning algorithms for data mining tasks—in an updated, interactive interface. Algorithms in toolkit cover: data pre-processing, classification, regression, clustering, association rules, visualization
