The aim of this book is to present statistical problems and methods in a friendly way to radiologists, emphasizing statistical issues and methods most frequently used in radiological studies (e.g., nonparametric tests, analysis of intra- and interobserver reproducibility, comparison of sensitivity and specificity among different imaging modality, difference between clinical and screening application of diagnostic tests, ect.). The tests will be presented starting from a radiological "problem" and all examples of statistical methods applications will be "radiological".

Research Methods in Radiology provides concise, practical insights on how to design clinical and experimental studies in diagnostic imaging. This unique resource encompasses contributions from leaders in academic radiology as well as top epidemiologists, biostatisticians, and librarians with vast multidisciplinary and radiology research experience. The material reflects years of expertise teaching core biostatistics in radiology principles to residents, fellows, radiologists, and epidemiologists. Given the vast amount of published information on research methodology and statistics in radiology, the authors' goal was to write a high-yield review and study tool rather than a comprehensive book. Key topics are succinctly addressed in each chapter, including measurements in radiology; decision analysis in radiology; and systemic reviews, evidence-based imaging, and knowledge translation. Online exercises related to each topic enable residents to prepare for radiology board examinations and research radiologists to apply knowledge to clinical studies. Key Highlights Introductory chapters on analysis of diagnostic tests, linear and logistic regression, meta-analysis, statistical inference, and economic evaluation provide easy-to-follow tutorials Each chapter includes learning objectives, basic concepts, supplementary tables, and ancillary online material Case studies with images, graphs, and tables highlight primary "take home" points Sample size calculations are illustrated for a wide range of research questions Code is included for use in R, free open-source software for statistical analysis This book is an indispensable review of research methodology for radiology students and residents. Practicing clinicians will also benefit from this precisely focused reference tool on clinical and experimental research.

Statistical evaluation of diagnostic performance in general and Receiver Operating Characteristic (ROC) analysis in particular are important for assessing the performance of medical tests and statistical classifiers, as well as for evaluating predictive models or algorithms. This book presents innovative approaches in ROC analysis, which are releva

Biostatistics for Oncologists is the first practical guide providing the essential biostatistical concepts, oncology-specific examples, and applicable problem sets for medical oncologists, radiation oncologists, and surgical oncologists. In addition, it serves as a review for medical oncology and radiation oncology residents or fellows preparing for in-service and board exams. All examples are relevant to oncology and demonstrate how to apply core conceptual knowledge and applicable methods related to hypothesis testing, correlation and regression, categorical data analysis and survival analysis to the field of oncology. The book also provides guidance on the fundamentals of study design and analysis. Written for oncologists by oncologists, this practical text demystifies challenging statistical concepts and provides concise direction on how to interpret, analyze, and critique data in oncology publications, as well as how to apply statistical knowledge to understanding, designing, and analyzing clinical trials. With practical problem sets and twenty-five multiple choice practice questions with answers, the book is an indispensable review for anyone preparing for in-service exams, boards, MOC, or looking to hone a lifelong skill. Key Features: Practically explains biostatistics concepts important for passing the hematology, medical oncology, and radiation oncology boards and MOC exams Provides guidance on how to read, understand, and critique data in oncology publications Gives relevant examples that are important for analyzing data in oncology, including the design and analysis of clinical trials Tests your comprehension of key biostatistical concepts with problem sets at the end of each section and a final section devoted to board-style multiple choice questions and answers Includes digital access to the eBook

The ability to analyze and interpret enormous amounts of data has become a prerequisite for success in allied healthcare and the health sciences. Now in its 11th edition, Biostatistics: A Foundation for Analysis in the Health Sciences continues to offer in-depth guidance toward biostatistical concepts, techniques, and practical applications in the modern healthcare setting. Comprehensive in scope yet detailed in coverage, this text helps students understand—and appropriately use—probability distributions, sampling distributions, estimation, hypothesis testing, variance analysis, regression, correlation analysis, and other statistical tools fundamental to the science and practice of medicine. Clearly-defined pedagogical tools help students stay up-to-date on new material, and an emphasis on statistical software allows faster, more accurate calculation while putting the focus on the underlying concepts rather than the math. Students develop highly relevant skills in inferential and differential statistical techniques, equipping them with the ability to organize, summarize, and interpret large bodies of data. Suitable for both graduate and advanced undergraduate coursework, this text retains the rigor required for use as a professional reference.

This book is a comprehensive guide to contrast-enhanced mammography (CEM), a novel advanced mammography technique using dual-energy mammography in combination with intravenous contrast administration in order to increase the diagnostic performance of digital mammography. Readers will find helpful information on the principles of CEM and indications for the technique. Detailed attention is devoted to image interpretation, with presentation of case examples and highlighting of pitfalls and artifacts. Other topics to be addressed include the establishment of a CEM program, the comparative merits of CEM and MRI, and the roles of CEM in screening populations and monitoring of response to neoadjuvant chemotherapy. CEM became commercially available in 2011 and is increasingly being used in clinical practice owing to its superiority over full-field digital mammography. This book will be an ideal source of knowledge and guidance for all who wish to start using the technique or to learn more about it.