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Author: Sergey Makarov Publisher: Springer Nature ISBN: 3030212939 Category : Technology & Engineering Languages : en Pages : 398
Book Description
This open access book describes modern applications of computational human modeling with specific emphasis in the areas of neurology and neuroelectromagnetics, depression and cancer treatments, radio-frequency studies and wireless communications. Special consideration is also given to the use of human modeling to the computational assessment of relevant regulatory and safety requirements. Readers working on applications that may expose human subjects to electromagnetic radiation will benefit from this book’s coverage of the latest developments in computational modelling and human phantom development to assess a given technology’s safety and efficacy in a timely manner. Describes construction and application of computational human models including anatomically detailed and subject specific models; Explains new practices in computational human modeling for neuroelectromagnetics, electromagnetic safety, and exposure evaluations; Includes a survey of modern applications for which computational human models are critical; Describes cellular-level interactions between the human body and electromagnetic fields.
Author: Sergey Makarov Publisher: Springer Nature ISBN: 3030212939 Category : Technology & Engineering Languages : en Pages : 398
Book Description
This open access book describes modern applications of computational human modeling with specific emphasis in the areas of neurology and neuroelectromagnetics, depression and cancer treatments, radio-frequency studies and wireless communications. Special consideration is also given to the use of human modeling to the computational assessment of relevant regulatory and safety requirements. Readers working on applications that may expose human subjects to electromagnetic radiation will benefit from this book’s coverage of the latest developments in computational modelling and human phantom development to assess a given technology’s safety and efficacy in a timely manner. Describes construction and application of computational human models including anatomically detailed and subject specific models; Explains new practices in computational human modeling for neuroelectromagnetics, electromagnetic safety, and exposure evaluations; Includes a survey of modern applications for which computational human models are critical; Describes cellular-level interactions between the human body and electromagnetic fields.
Author: Mithat Gonen Publisher: SAS Press ISBN: 9781599942988 Category : Computers Languages : en Pages : 0
Book Description
As a diagnostic decision-making tool, receiver operating characteristic (ROC) curves provide a comprehensive and visually attractive way to summarize the accuracy of predictions. They are used extensively in medical diagnosis and increasingly in fields such as data mining, credit scoring, weather forecasting, and psychometry. In Analyzing Receiver Operating Characteristic Curves with SAS, author Mithat Gonen illustrates the many existing SAS procedures that can be tailored to produce ROC curves and expands upon further analyses using other SAS procedures and macros. Both parametric and nonparametric methods for analyzing ROC curves are covered in detail. Topics addressed include: Appropriate methods for binary, ordinal, and continuous measures Computations using PROC FREQ, PROC LOGISTIC, PROC NLMIXED, and macros Comparing the ROC curves of several markers and adjusting them for covariates ROC curves with censored data Using the ROC curve for evaluating multivariable prediction models via bootstrap and cross-validation ROC curves in SAS Enterprise Miner And more! Written for any statistician interested in learning more about ROC curve methodology, the book assumes readers have a basic understanding of regression procedures and moderate familiarity with Base SAS and SAS/STAT. Some familiarity with SAS/GRAPH is helpful but not essential. This book is part of the SAS Press program.
Author: Xiao-Hua Zhou Publisher: John Wiley & Sons ISBN: 1118626044 Category : Medical Languages : en Pages : 597
Book Description
Praise for the First Edition " . . . the book is a valuable addition to the literature in the field, serving as a much-needed guide for both clinicians and advanced students."—Zentralblatt MATH A new edition of the cutting-edge guide to diagnostic tests in medical research In recent years, a considerable amount of research has focused on evolving methods for designing and analyzing diagnostic accuracy studies. Statistical Methods in Diagnostic Medicine, Second Edition continues to provide a comprehensive approach to the topic, guiding readers through the necessary practices for understanding these studies and generalizing the results to patient populations. Following a basic introduction to measuring test accuracy and study design, the authors successfully define various measures of diagnostic accuracy, describe strategies for designing diagnostic accuracy studies, and present key statistical methods for estimating and comparing test accuracy. Topics new to the Second Edition include: Methods for tests designed to detect and locate lesions Recommendations for covariate-adjustment Methods for estimating and comparing predictive values and sample size calculations Correcting techniques for verification and imperfect standard biases Sample size calculation for multiple reader studies when pilot data are available Updated meta-analysis methods, now incorporating random effects Three case studies thoroughly showcase some of the questions and statistical issues that arise in diagnostic medicine, with all associated data provided in detailed appendices. A related web site features Fortran, SAS®, and R software packages so that readers can conduct their own analyses. Statistical Methods in Diagnostic Medicine, Second Edition is an excellent supplement for biostatistics courses at the graduate level. It also serves as a valuable reference for clinicians and researchers working in the fields of medicine, epidemiology, and biostatistics.
Author: Wojtek J. Krzanowski Publisher: CRC Press ISBN: 1439800227 Category : Business & Economics Languages : en Pages : 256
Book Description
Since ROC curves have become ubiquitous in many application areas, the various advances have been scattered across disparate articles and texts. ROC Curves for Continuous Data is the first book solely devoted to the subject, bringing together all the relevant material to provide a clear understanding of how to analyze ROC curves.The fundamenta
Author: Kelly H. Zou Publisher: CRC Press ISBN: 1439812233 Category : Mathematics Languages : en Pages : 243
Book Description
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
Author: C. Huber-Carol Publisher: Springer Science & Business Media ISBN: 1461201039 Category : Mathematics Languages : en Pages : 512
Book Description
The 37 expository articles in this volume provide broad coverage of important topics relating to the theory, methods, and applications of goodness-of-fit tests and model validity. The book is divided into eight parts, each of which presents topics written by expert researchers in their areas. Key features include: * state-of-the-art exposition of modern model validity methods, graphical techniques, and computer-intensive methods * systematic presentation with sufficient history and coverage of the fundamentals of the subject * exposure to recent research and a variety of open problems * many interesting real life examples for practitioners * extensive bibliography, with special emphasis on recent literature * subject index This comprehensive reference work will serve the statistical and applied mathematics communities as well as practitioners in the field.
Author: Margaret Sullivan Pepe Publisher: OUP Oxford ISBN: 019158861X Category : Medical Languages : en Pages : 319
Book Description
This book describes statistical techniques for the design and evaluation of research studies on medical diagnostic tests, screening tests, biomarkers and new technologies for classification and prediction in medicine.
Author: Gavin Hackeling Publisher: Packt Publishing Ltd ISBN: 1788298497 Category : Computers Languages : en Pages : 249
Book Description
Use scikit-learn to apply machine learning to real-world problems About This Book Master popular machine learning models including k-nearest neighbors, random forests, logistic regression, k-means, naive Bayes, and artificial neural networks Learn how to build and evaluate performance of efficient models using scikit-learn Practical guide to master your basics and learn from real life applications of machine learning Who This Book Is For This book is intended for software engineers who want to understand how common machine learning algorithms work and develop an intuition for how to use them, and for data scientists who want to learn about the scikit-learn API. Familiarity with machine learning fundamentals and Python are helpful, but not required. What You Will Learn Review fundamental concepts such as bias and variance Extract features from categorical variables, text, and images Predict the values of continuous variables using linear regression and K Nearest Neighbors Classify documents and images using logistic regression and support vector machines Create ensembles of estimators using bagging and boosting techniques Discover hidden structures in data using K-Means clustering Evaluate the performance of machine learning systems in common tasks In Detail Machine learning is the buzzword bringing computer science and statistics together to build smart and efficient models. Using powerful algorithms and techniques offered by machine learning you can automate any analytical model. This book examines a variety of machine learning models including popular machine learning algorithms such as k-nearest neighbors, logistic regression, naive Bayes, k-means, decision trees, and artificial neural networks. It discusses data preprocessing, hyperparameter optimization, and ensemble methods. You will build systems that classify documents, recognize images, detect ads, and more. You will learn to use scikit-learn's API to extract features from categorical variables, text and images; evaluate model performance, and develop an intuition for how to improve your model's performance. By the end of this book, you will master all required concepts of scikit-learn to build efficient models at work to carry out advanced tasks with the practical approach. Style and approach This book is motivated by the belief that you do not understand something until you can describe it simply. Work through toy problems to develop your understanding of the learning algorithms and models, then apply your learnings to real-life problems.
Author: Sergey Makarov
Author: Sergey Makarov
Author: Matthew E. Cross
Author: Mithat Gonen
Author: Xiao-Hua Zhou
Author: Wojtek J. Krzanowski
Author: Ling Liu
Author: Kelly H. Zou
Author: C. Huber-Carol
Author: Margaret Sullivan Pepe
Author: Gavin Hackeling