Download or read book Data Analysis in Medicine and Health using R written by Kamarul Imran Musa and published by CRC Press. This book was released on 2023-09-12 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data analysis plays a vital role in guiding medical treatment plans, patient care, and the formulation of control and prevention policies in the field of healthcare. In today's era, researchers in these domains require a firm grasp of data, statistical concepts, and programming skills due to the increasing complexity of data. Reproducible analyses and cutting-edge statistical methods are becoming increasingly necessary. This book, which is both comprehensive and highly practical, addresses these challenges by laying a solid foundation of data and statistical theory for readers. Subsequently, it equips them with practical skills to conduct analyses using the powerful R programming language, widely used by statisticians. The book takes a gentle approach to help readers navigate data and statistical analysis using R, minimizing the learning curve. RStudio is used as the integrated development environment (IDE) for enhanced productivity for readers to run their R codes. Following a logical sequence commonly applied in medical and health research, the book covers fundamental concepts of data analysis and statistical modeling techniques. It provides readers, including those with limited statistical knowledge and programming skills, with hands-on experience through R programming. The online version of this book is available on bookdown.org, a publishing platform provided by RStudio, PBC specifically designed to host books written using the "bookdown" package in R. Additionally, all R codes and datasets in this book can be found on the author's GitHub repository.

Download or read book R for Health Data Science written by Ewen Harrison and published by CRC Press. This book was released on 2020-12-31 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this age of information, the manipulation, analysis, and interpretation of data have become a fundamental part of professional life; nowhere more so than in the delivery of healthcare. From the understanding of disease and the development of new treatments, to the diagnosis and management of individual patients, the use of data and technology is now an integral part of the business of healthcare. Those working in healthcare interact daily with data, often without realising it. The conversion of this avalanche of information to useful knowledge is essential for high-quality patient care. R for Health Data Science includes everything a healthcare professional needs to go from R novice to R guru. By the end of this book, you will be taking a sophisticated approach to health data science with beautiful visualisations, elegant tables, and nuanced analyses. Features Provides an introduction to the fundamentals of R for healthcare professionals Highlights the most popular statistical approaches to health data science Written to be as accessible as possible with minimal mathematics Emphasises the importance of truly understanding the underlying data through the use of plots Includes numerous examples that can be adapted for your own data Helps you create publishable documents and collaborate across teams With this book, you are in safe hands – Prof. Harrison is a clinician and Dr. Pius is a data scientist, bringing 25 years’ combined experience of using R at the coal face. This content has been taught to hundreds of individuals from a variety of backgrounds, from rank beginners to experts moving to R from other platforms.

Download or read book Data Analytics in Medicine Concepts Methodologies Tools and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2019-12-06 with total page 2071 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advancements in data science have created opportunities to sort, manage, and analyze large amounts of data more effectively and efficiently. Applying these new technologies to the healthcare industry, which has vast quantities of patient and medical data and is increasingly becoming more data-reliant, is crucial for refining medical practices and patient care. Data Analytics in Medicine: Concepts, Methodologies, Tools, and Applications is a vital reference source that examines practical applications of healthcare analytics for improved patient care, resource allocation, and medical performance, as well as for diagnosing, predicting, and identifying at-risk populations. Highlighting a range of topics such as data security and privacy, health informatics, and predictive analytics, this multi-volume book is ideally designed for doctors, hospital administrators, nurses, medical professionals, IT specialists, computer engineers, information technologists, biomedical engineers, data-processing specialists, healthcare practitioners, academicians, and researchers interested in current research on the connections between data analytics in the field of medicine.

Download or read book Data Analysis for the Life Sciences with R written by Rafael A. Irizarry and published by CRC Press. This book was released on 2016-10-04 with total page 461 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers several of the statistical concepts and data analytic skills needed to succeed in data-driven life science research. The authors proceed from relatively basic concepts related to computed p-values to advanced topics related to analyzing highthroughput data. They include the R code that performs this analysis and connect the lines of code to the statistical and mathematical concepts explained.

Download or read book Healthcare Data Analytics written by Chandan K. Reddy and published by CRC Press. This book was released on 2015-06-23 with total page 756 pages. Available in PDF, EPUB and Kindle. Book excerpt: At the intersection of computer science and healthcare, data analytics has emerged as a promising tool for solving problems across many healthcare-related disciplines. Supplying a comprehensive overview of recent healthcare analytics research, Healthcare Data Analytics provides a clear understanding of the analytical techniques currently available

Download or read book Biostatistics and Computer based Analysis of Health Data using R written by Christophe Lalanne and published by Elsevier. This book was released on 2016-07-13 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biostatistics and Computer-Based Analysis of Health Data Using the R Software addresses the concept that many of the actions performed by statistical software comes back to the handling, manipulation, or even transformation of digital data. It is therefore of primary importance to understand how statistical data is displayed and how it can be exploited by software such as R. In this book, the authors explore basic and variable commands, sample comparisons, analysis of variance, epidemiological studies, and censored data. With proposed applications and examples of commands following each chapter, this book allows readers to apply advanced statistical concepts to their own data and software. Features useful commands for describing a data table composed made up of quantitative and qualitative variables Includes measures of association encountered in epidemiological studies, odds ratio, relative risk, and prevalence Presents an analysis of censored data, the key main tests associated with the construction of a survival curve (log-rank test or Wilcoxon), and the Cox regression model

Download or read book Healthcare Analytics written by Hui Yang and published by John Wiley & Sons. This book was released on 2016-10-10 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt: Features of statistical and operational research methods and tools being used to improve the healthcare industry With a focus on cutting-edge approaches to the quickly growing field of healthcare, Healthcare Analytics: From Data to Knowledge to Healthcare Improvement provides an integrated and comprehensive treatment on recent research advancements in data-driven healthcare analytics in an effort to provide more personalized and smarter healthcare services. Emphasizing data and healthcare analytics from an operational management and statistical perspective, the book details how analytical methods and tools can be utilized to enhance healthcare quality and operational efficiency. Organized into two main sections, Part I features biomedical and health informatics and specifically addresses the analytics of genomic and proteomic data; physiological signals from patient-monitoring systems; data uncertainty in clinical laboratory tests; predictive modeling; disease modeling for sepsis; and the design of cyber infrastructures for early prediction of epidemic events. Part II focuses on healthcare delivery systems, including system advances for transforming clinic workflow and patient care; macro analysis of patient flow distribution; intensive care units; primary care; demand and resource allocation; mathematical models for predicting patient readmission and postoperative outcome; physician–patient interactions; insurance claims; and the role of social media in healthcare. Healthcare Analytics: From Data to Knowledge to Healthcare Improvement also features: • Contributions from well-known international experts who shed light on new approaches in this growing area • Discussions on contemporary methods and techniques to address the handling of rich and large-scale healthcare data as well as the overall optimization of healthcare system operations • Numerous real-world examples and case studies that emphasize the vast potential of statistical and operational research tools and techniques to address the big data environment within the healthcare industry • Plentiful applications that showcase analytical methods and tools tailored for successful healthcare systems modeling and improvement The book is an ideal reference for academics and practitioners in operations research, management science, applied mathematics, statistics, business, industrial and systems engineering, healthcare systems, and economics. Healthcare Analytics: From Data to Knowledge to Healthcare Improvement is also appropriate for graduate-level courses typically offered within operations research, industrial engineering, business, and public health departments.

Download or read book Biostatistics for Epidemiology and Public Health Using R written by Bertram K.C. Chan, PhD and published by Springer Publishing Company. This book was released on 2015-11-05 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since it first appeared in 1996, the open-source programming language R has become increasingly popular as an environment for statistical analysis and graphical output. This is the first textbook to present classical biostatistical analysis for epidemiology and related public health sciences to students using the R language. Based on the assumption that readers have minimal familiarity with statistical concepts, the author uses a step-by-step approach to building skills. The text encompasses biostatistics from basic descriptive and quantitative statistics to survival analysis and missing data analysis in epidemiology. Illustrative examples, including real-life research problems drawn from such areas as nutrition, environmental health, and behavioral health, engage students and reinforce the understanding of R. These examples illustrate the replication of R for biostatistical calculations and graphical display of results. The text covers both essential and advanced techniques and applications in biostatistics that are relevant to epidemiology. Also included are an instructor's guide, student solutions manual, and downloadable data sets. Key Features: First overview biostatistics textbook for epidemiology and public health that uses the open-source R program Covers essential and advanced techniques and applications in biostatistics as relevant to epidemiology Features abundant examples to illustrate the application of R language for biostatistical calculations and graphical displays of results Includes instructor's guide, student solutions manual, and downloadable data sets.

Download or read book Analyzing Health Data in R for SAS Users written by Monika Maya Wahi and published by CRC Press. This book was released on 2017-11-22 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analyzing Health Data in R for SAS Users is aimed at helping health data analysts who use SAS accomplish some of the same tasks in R. It is targeted to public health students and professionals who have a background in biostatistics and SAS software, but are new to R. For professors, it is useful as a textbook for a descriptive or regression modeling class, as it uses a publicly-available dataset for examples, and provides exercises at the end of each chapter. For students and public health professionals, not only is it a gentle introduction to R, but it can serve as a guide to developing the results for a research report using R software. Features: Gives examples in both SAS and R Demonstrates descriptive statistics as well as linear and logistic regression Provides exercise questions and answers at the end of each chapter Uses examples from the publicly available dataset, Behavioral Risk Factor Surveillance System (BRFSS) 2014 data Guides the reader on producing a health analysis that could be published as a research report Gives an example of hypothesis-driven data analysis Provides examples of plots with a color insert

Download or read book Real World Health Care Data Analysis written by Douglas Faries and published by SAS Institute. This book was released on 2020-01-15 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover best practices for real world data research with SAS code and examples Real world health care data is common and growing in use with sources such as observational studies, patient registries, electronic medical record databases, insurance healthcare claims databases, as well as data from pragmatic trials. This data serves as the basis for the growing use of real world evidence in medical decision-making. However, the data itself is not evidence. Analytical methods must be used to turn real world data into valid and meaningful evidence. Real World Health Care Data Analysis: Causal Methods and Implementation Using SAS brings together best practices for causal comparative effectiveness analyses based on real world data in a single location and provides SAS code and examples to make the analyses relatively easy and efficient. The book focuses on analytic methods adjusted for time-independent confounding, which are useful when comparing the effect of different potential interventions on some outcome of interest when there is no randomization. These methods include: propensity score matching, stratification methods, weighting methods, regression methods, and approaches that combine and average across these methods methods for comparing two interventions as well as comparisons between three or more interventions algorithms for personalized medicine sensitivity analyses for unmeasured confounding

Download or read book Healthcare Data Analytics and Management written by Nilanjan Dey and published by Academic Press. This book was released on 2018-11-15 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Healthcare Data Analytics and Management help readers disseminate cutting-edge research that delivers insights into the analytic tools, opportunities, novel strategies, techniques and challenges for handling big data, data analytics and management in healthcare. As the rapidly expanding and heterogeneous nature of healthcare data poses challenges for big data analytics, this book targets researchers and bioengineers from areas of machine learning, data mining, data management, and healthcare providers, along with clinical researchers and physicians who are interested in the management and analysis of healthcare data. Covers data analysis, management and security concepts and tools in the healthcare domain Highlights electronic medical health records and patient information records Discusses the different techniques to integrate Big data and Internet-of-Things in healthcare, including machine learning and data mining Includes multidisciplinary contributions in relation to healthcare applications and challenges

Download or read book R for Medicine and Biology written by Paul D. Lewis and published by Jones & Bartlett Learning. This book was released on 2009-05-08 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: R is quickly becoming the number one choice for users in the fields of biology, medicine, and bioinformatics as their main means of storing, processing, sharing, and analyzing biomedical data. R for Medicine and Biology is a step-by-step guide through the use of the statistical environment R, as used in a biomedical domain. Ideal for healthcare professionals, scientists, informaticists, and statistical experts, this resource will provide even the novice programmer with the tools necessary to process and analyze their data using the R environment. Introductory chapters guide readers in how to obtain, install, and become familiar with R and provide a clear introduction to the programming language using numerous worked examples. Later chapters outline how R can be used, not just for biomedical data analysis, but also as an environment for the processing, storing, reporting, and sharing of data and results. The remainder of the book explores areas of R application to common domains of biomedical informatics, including imaging, statistical analysis, data mining/modeling, pathology informatics, epidemiology, clinical trials, and metadata usage. R for Medicine and Biology will provide you with a single desk reference for the R environment and its many capabilities.

Download or read book Big Data Analytics in Healthcare written by Anand J. Kulkarni and published by Springer Nature. This book was released on 2019-10-01 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes state-of-the-art discussions on various issues and aspects of the implementation, testing, validation, and application of big data in the context of healthcare. The concept of big data is revolutionary, both from a technological and societal well-being standpoint. This book provides a comprehensive reference guide for engineers, scientists, and students studying/involved in the development of big data tools in the areas of healthcare and medicine. It also features a multifaceted and state-of-the-art literature review on healthcare data, its modalities, complexities, and methodologies, along with mathematical formulations. The book is divided into two main sections, the first of which discusses the challenges and opportunities associated with the implementation of big data in the healthcare sector. In turn, the second addresses the mathematical modeling of healthcare problems, as well as current and potential future big data applications and platforms.

Download or read book Health Services Research and Analytics Using Excel written by Nalin Johri, PhD, MPH and published by Springer Publishing Company. This book was released on 2020-02-01 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: Your all-in-one resource for quantitative, qualitative, and spatial analyses in Excel® using current real-world healthcare datasets. Health Services Research and Analytics Using Excel® is a practical resource for graduate and advanced undergraduate students in programs studying healthcare administration, public health, and social work as well as public health workers and healthcare managers entering or working in the field. This book provides one integrated, application-oriented resource for common quantitative, qualitative, and spatial analyses using only Excel. With an easy-to-follow presentation of qualitative and quantitative data, students can foster a balanced decision-making approach to financial data, patient statistical data and utilization information, population health data, and quality metrics while cultivating analytical skills that are necessary in a data-driven healthcare world. Whereas Excel is typically considered limited to quantitative application, this book expands into other Excel applications based on spatial analysis and data visualization represented through 3D Maps as well as text analysis using the free add-in in Excel. Chapters cover the important methods and statistical analysis tools that a practitioner will face when navigating and analyzing data in the public domain or from internal data collection at their health services organization. Topics covered include importing and working with data in Excel; identifying, categorizing, and presenting data; setting bounds and hypothesis testing; testing the mean; checking for patterns; data visualization and spatial analysis; interpreting variance; text analysis; and much more. A concise overview of research design also provides helpful background on how to gather and measure useful data prior to analyzing in Excel. Because Excel is the most common data analysis software used in the workplace setting, all case examples, exercises, and tutorials are provided with the latest updates to the Excel software from Office365 ProPlus® and newer versions, including all important “Add-ins” such as 3D Maps, MeaningCloud, and Power Pivots, among others. With numerous practice problems and over 100 step-by-step videos, Health Services Research and Analytics Using Excel® is an extremely practical tool for students and health service professionals who must know how to work with data, how to analyze it, and how to use it to improve outcomes unique to healthcare settings. Key Features: Provides a competency-based analytical approach to health services research using Excel Includes applications of spatial analysis and data visualization tools based on 3D Maps in Excel Lists select sources of useful national healthcare data with descriptions and website information Chapters contain case examples and practice problems unique to health services All figures and videos are applicable to Office365 ProPlus Excel and newer versions Contains over 100 step-by-step videos of Excel applications covered in the chapters and provides concise video tutorials demonstrating solutions to all end-of-chapter practice problems Robust Instructor ancillary package that includes Instructor’s Manual, PowerPoints, and Test Bank

Download or read book Exploratory Data Analytics for Healthcare written by R. Lakshmana Kumar and published by CRC Press. This book was released on 2021-12-24 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exploratory data analysis helps to recognize natural patterns hidden in the data. This book describes the tools for hypothesis generation by visualizing data through graphical representation and provides insight into advanced analytics concepts in an easy way. The book addresses the complete data visualization technologies workflow, explores basic and high-level concepts of computer science and engineering in medical science, and provides an overview of the clinical scientific research areas that enables smart diagnosis equipment. It will discuss techniques and tools used to explore large volumes of medical data and offers case studies that focus on the innovative technological upgradation and challenges faced today. The primary audience for the book includes specialists, researchers, graduates, designers, experts, physicians, and engineers who are doing research in this domain.

Download or read book Healthcare Analytics for Quality and Performance Improvement written by Trevor L. Strome and published by John Wiley & Sons. This book was released on 2013-10-02 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: Improve patient outcomes, lower costs, reduce fraud—all with healthcare analytics Healthcare Analytics for Quality and Performance Improvement walks your healthcare organization from relying on generic reports and dashboards to developing powerful analytic applications that drive effective decision-making throughout your organization. Renowned healthcare analytics leader Trevor Strome reveals in this groundbreaking volume the true potential of analytics to harness the vast amounts of data being generated in order to improve the decision-making ability of healthcare managers and improvement teams. Examines how technology has impacted healthcare delivery Discusses the challenge facing healthcare organizations: to leverage advances in both clinical and information technology to improve quality and performance while containing costs Explores the tools and techniques to analyze and extract value from healthcare data Demonstrates how the clinical, business, and technology components of healthcare organizations (HCOs) must work together to leverage analytics Other industries are already taking advantage of big data. Healthcare Analytics for Quality and Performance Improvement helps the healthcare industry make the most of the precious data already at its fingertips for long-overdue quality and performance improvement.

Download or read book Data Analytics in Healthcare Research written by Ryan Sandefer and published by . This book was released on 2015-12-08 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: