"e;Biomedical Imaging: Principles and Advancements"e; offers a captivating exploration of the intricate landscapes within the human body, revealing the transformative power of biomedical imaging.
The get-it-over-with-quickly approach to statistics has been encouraged - and often necessitated - by the short time allotted to it in most curriculums.
Strategic decision-making focusing on economics is the fundamental requirement to generate efficiency and improve productivity in any manufacturing environment.
Containing method descriptions and step-by-step procedures, the Spatial Epidemiological Approaches in Disease Mapping and Analysis equips readers with skills to prepare health-related data in the proper format, process these data using relevant functions and software, and display the results as mapped or statistical summaries.
Handbook of Spatial Epidemiology explains how to model epidemiological problems and improve inference about disease etiology from a geographical perspective.
In recent decades, there has been enormous growth in biologics research and development, with the accompanying development of biological assays for emerging products.
Introduction to Regression Methods for Public Health Using R teaches regression methods for continuous, binary, ordinal, and time-to-event outcomes using R as a tool.
This concise guide equips readers with the essential skills required to analyze and critically appraise health research evidence, an integral element to evidence-based practice and professional development.
Introductory Statistics for the Health Sciences takes students on a journey to a wilderness where science explores the unknown, providing students with a strong, practical foundation in statistics.
This is the second edition of an introductory text that describes the principles of invariant measurement; how invariant measurement can be achieved using Rasch measurement theory; and how to use invariant measurement to solve a variety of measurement problems in the social, behavioral, and health sciences.
This book investigates the experiences of women in Zimbabwe facing COVID-19 and gender-based violence, arguing that the insights from this extremely tough period could be used as a springboard for positive legal, cultural and policy changes.
Wide-Ranging Coverage of Parametric Modeling in Linear and Nonlinear Mixed Effects ModelsMixed Effects Models for the Population Approach: Models, Tasks, Methods and Tools presents a rigorous framework for describing, implementing, and using mixed effects models.
Providing key information on how to work with research data, Introduction to Data Technologies presents ideas and techniques for performing critical, behind-the-scenes tasks that take up so much time and effort yet typically receive little attention in formal education.
An in-depth overview on the demo-graphic changes occurring world-wide and the repercussions this is having on the pattern of vector-borne disease is pre-sented in this book.
Although classical electromagnetic (EM) field theory is typically embedded in vector calculus and differential equations, many of the basic concepts and characteristics can be understood with precursory mathematical knowledge.
Get Up to Speed on Many Types of Adaptive DesignsSince the publication of the first edition, there have been remarkable advances in the methodology and application of adaptive trials.
This new edition of Viral Pandemics illuminates how the increasing emergence of novel viruses has combined with intensifying global interconnectedness to create an escalating spiral of viral disease.
Power and Sample Size in R guides the reader through power and sample size calculations for a wide variety of study outcomes and designs and illustrates their implementation in R software.
Written with medical statisticians and medical researchers in mind, this intermediate-level reference explores the use of SAS for analyzing medical data.
All the Essentials to Start Using Adaptive Designs in No TimeCompared to traditional clinical trial designs, adaptive designs often lead to increased success rates in drug development at reduced costs and time.
Artificial Intelligence Technology in Healthcare: Security and Privacy Issues focuses on current issues with patients' privacy and data security including data breaches in healthcare organizations, unauthorized access to patients' information, and medical identity theft.
While biomedical researchers may be able to follow instructions in the manuals accompanying the statistical software packages, they do not always have sufficient knowledge to choose the appropriate statistical methods and correctly interpret their results.
