Statistical Modeling in Biomedical Research: Contemporary Topics and Voices in the Field (Emerging Topics in Statistics and Biostatistics) - Hardcover

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Professor Yichuan Zhao is a professor of statistics at Georgia State University. He has a joint appointment as associate member of the Neuroscience Institute, and he is also an affiliated faculty member at the School of Public Health at Georgia State University.  His current research interests focus on survival analysis, empirical likelihood method, nonparametric statistics, statistical analysis of ROC curves, bioinformatics, Monte Carlo methods, high-dimensional data analysis, and statistical modeling of fuzzy systems. He has published over 90 research articles in statistics and has co-edited three books on statistics, biostatistics & data science. In addition, he has been invited to deliver more than 180 research talks nationally and internationally. Dr. Zhao has organized the Workshop Series on Biostatistics and Bioinformatics since its initiation in 2012. He also organized the 25th ICSA Applied Statistics Symposium in Atlanta as a chair of the organizing committee to great success. He is currently serving as associate editor, or on the editorial board, for several statistical journals. Dr. Zhao is an elected member of the International Statistical Institute. 

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. 

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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.