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© 2020

Statistical Modeling in Biomedical Research

Contemporary Topics and Voices in the Field

  • Yichuan Zhao
  • Ding-Geng (Din) Chen
Book

Part of the Emerging Topics in Statistics and Biostatistics book series (ETSB)

Table of contents

  1. Front Matter
    Pages i-xviii
  2. Next Generation Sequence Data Analysis

    1. Front Matter
      Pages 1-1
    2. Liyang Diao, Ying Zhu, Nenad Sestan, Hongyu Zhao
      Pages 3-22
    3. Hsin-Hsiung Huang, Aubrey Condor, Helen J. Huang
      Pages 23-35
    4. Wenyu Zhang, Jiaxuan Wangwu, Zhixiang Lin
      Pages 37-64
  3. Deep Learning, Precision Medicine and Applications

    1. Front Matter
      Pages 93-93
    2. Claudia Solís-Lemus, Xin Ma, Maxwell Hostetter II, Suprateek Kundu, Peng Qiu, Daniel Pimentel-Alarcón
      Pages 95-104
    3. Eun Jeong Oh, Min Qian, Ken Cheung, David C. Mohr
      Pages 105-123
  4. Large Scale Data Analysis and Its Applications

    1. Front Matter
      Pages 143-143
    2. Duolin Wang, Juexin Wang, Yu Chen, Sean Yang, Qin Zeng, Jingdong Liu et al.
      Pages 173-196
    3. Xiaosong Han, Haiyan Zhao, Hao Xu, Yun Yang, Yanchun Liang, Dong Xu
      Pages 197-212
    4. Junxian Geng, Elizabeth H. Slate
      Pages 213-232
  5. Biomedical Research and the Modelling

    1. Front Matter
      Pages 233-233
    2. Moo K. Chung, Nagesh Adluru, Houri K. Vorperian
      Pages 235-261
    3. Chuanping Yu, Xiaoming Huo
      Pages 263-308

About this book

Introduction

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.

Keywords

high dimensional statistical methods survival analysis feature selection gene expression analysis next generation sequence complex data analysis data mining classification support vector machine

Editors and affiliations

  • Yichuan Zhao
    • 1
  • Ding-Geng (Din) Chen
    • 2
  1. 1.Math and Statistics, 1342Georgia State UniversityAtlantaUSA
  2. 2.School of Social WorkUniversity of North CarolinaChapel HillUSA

About the editors

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. 

Bibliographic information