Intelligent Data Analysis in Medicine and Pharmacology, Nada Lavra?; Elpida Keravnou-Papailiou; Blaz Zupan
Автор: Hsiang-Cheh Huang; Wai-Chi Fang Название: Intelligent Multimedia Data Hiding ISBN: 364242922X ISBN-13(EAN): 9783642429224 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book lays out all the latest research in the area of multimedia data hiding. It moves on to cover the recent advances in multimedia signal processing, before presenting information hiding techniques including steganography, secret sharing and watermarking.
Автор: Xiaochun Li; Ronghui Xu Название: High-Dimensional Data Analysis in Cancer Research ISBN: 1441924140 ISBN-13(EAN): 9781441924148 Издательство: Springer Рейтинг: Цена: 19589.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume presents the systematic and analytical approaches and strategies from both biostatistics and bioinformatics to the analysis of correlated and high-dimensional data. It poses new challenges and calls for scalable solutions.
Автор: Jos? Luis Oliveira; V?ctor Maojo; Fernando Martin- Название: Biological and Medical Data Analysis ISBN: 3540296743 ISBN-13(EAN): 9783540296744 Издательство: Springer Рейтинг: Цена: 12157.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Constitutes the refereed proceedings of the 6th International Symposium on Biological and Medical Data Analysis, ISBMDA 2005, held in Aveiro, Portugal, in November 2005. This book is organized in topical sections on medical databases and information systems, data analysis and image processing, decision support systems, and more.
Автор: Hagger Johnson Gareth Название: Introduction to Research Methods and Data Analysis in the He ISBN: 0273763849 ISBN-13(EAN): 9780273763840 Издательство: Taylor&Francis Рейтинг: Цена: 7501.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This text presents a balanced blend of quantitative research methods, and the most widely used techniques for collecting and analysing data in the health sciences. Highly practical in nature, the book guides you, step-by-step, through the research process, and covers both the consumption and the production of research and data analysis.
Автор: Xiao–Hua Zhou,Chuan Zhou,Danping Lui,Xaiobo Ding Название: Applied Missing Data Analysis in the Health Sciences ISBN: 0470523816 ISBN-13(EAN): 9780470523810 Издательство: Wiley Рейтинг: Цена: 15515.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a modern, hands-on guide to the essential concepts and ideas for analyzing data with missing observations in the field of biostatistics. It acknowledges the limitations of established techniques and provides concrete applications of newly developed methods.
Описание: Next Generation Sequencing (NGS) is the latest high throughput technology to revolutionize genomic research. NGS generates massive genomic datasets that play a key role in the big data phenomenon that surrounds us today. To extract signals from high-dimensional NGS data and make valid statistical inferences and predictions, novel data analytic and statistical techniques are needed. This book contains 20 chapters written by prominent statisticians working with NGS data. The topics range from basic preprocessing and analysis with NGS data to more complex genomic applications such as copy number variation and isoform expression detection. Research statisticians who want to learn about this growing and exciting area will find this book useful. In addition, many chapters from this book could be included in graduate-level classes in statistical bioinformatics for training future biostatisticians who will be expected to deal with genomic data in basic biomedical research, genomic clinical trials and personalized medicine. About the editors: Somnath Datta is Professor and Vice Chair of Bioinformatics and Biostatistics at the University of Louisville. He is Fellow of the American Statistical Association, Fellow of the Institute of Mathematical Statistics and Elected Member of the International Statistical Institute. He has contributed to numerous research areas in Statistics, Biostatistics and Bioinformatics. Dan Nettleton is Professor and Laurence H. Baker Endowed Chair of Biological Statistics in the Department of Statistics at Iowa State University. He is Fellow of the American Statistical Association and has published research on a variety of topics in statistics, biology and bioinformatics.
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