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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

  6. Survival Analysis with Complex Data Structure and Its Applications

  7. Back Matter
    Pages 483-491

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

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-030-33416-1
  • Copyright Information Springer Nature Switzerland AG 2020
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-030-33415-4
  • Online ISBN 978-3-030-33416-1
  • Series Print ISSN 2524-7735
  • Series Online ISSN 2524-7743
  • Buy this book on publisher's site
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