Overview
- Includes a foundational overview of modeling in biomedical research to guide the reader in learning efficiently
- Covers machine learning, GWAS data analysis, sequence analysis, and survival analysis in the big data era
- Includes innovative statistical methods and applications in biomedical research
Part of the book series: Emerging Topics in Statistics and Biostatistics (ETSB)
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Table of contents (19 chapters)
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Biomedical Research and the Modelling
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Survival Analysis with Complex Data Structure and Its Applications
Keywords
About this book
This edited collection discusses the emerging topics in statistical modeling for biomedical research. Leading experts in the frontiers of biostatistics and biomedical research discuss the statistical procedures, useful methods, and their novel applications in biostatistics research. Interdisciplinary in scope, the volume as a whole reflects the latest advances in statistical modeling in biomedical research, identifies impactful new directions, and seeks to drive the field forward. It also fosters the interaction of scholars in the arena, offering great opportunities to stimulate further collaborations. This book will appeal to industry data scientists and statisticians, researchers, and graduate students in biostatistics and biomedical science. It covers topics in:
- Next generation sequence data analysis
- Deep learning, precision medicine, and their applications
- Large scale data analysis and its applications
- Biomedical research and modeling
- Survival analysis with complex data structure and its applications.
Editors and Affiliations
About the editors
Professor (Din) Ding-Geng Chen is a fellow of the American Statistical Association and currently the Wallace H. Kuralt Distinguished Professor at the University of North Carolina at Chapel Hill, and an extra-ordinary professor at the University of Pretoria. He was a professor at the University of Rochester and the Karl E. Peace Endowed Eminent Scholar Chair in biostatistics at Georgia Southern University. He is also a senior consultant for biopharmaceutical and government agencies, with extensive expertise in clinical trial biostatistics and public health statistics. Professor Chen has written more than 200 refereed publications and has co-authored/co-edited 28 books on clinical trial methodology, meta-analysis, causal inference, and public health statistics.
Bibliographic Information
Book Title: Statistical Modeling in Biomedical Research
Book Subtitle: Contemporary Topics and Voices in the Field
Editors: Yichuan Zhao, Ding-Geng (Din) Chen
Series Title: Emerging Topics in Statistics and Biostatistics
DOI: https://doi.org/10.1007/978-3-030-33416-1
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-33415-4Published: 20 March 2020
Softcover ISBN: 978-3-030-33418-5Published: 20 March 2021
eBook ISBN: 978-3-030-33416-1Published: 19 March 2020
Series ISSN: 2524-7735
Series E-ISSN: 2524-7743
Edition Number: 1
Number of Pages: XVIII, 491
Number of Illustrations: 28 b/w illustrations, 79 illustrations in colour
Topics: Statistics for Life Sciences, Medicine, Health Sciences, Biostatistics, Big Data/Analytics, Data Mining and Knowledge Discovery