Health Informatics Data Analysis

Methods and Examples

  • Dong Xu
  • May D. Wang
  • Fengfeng Zhou
  • Yunpeng Cai

Part of the Health Information Science book series (HIS)

Table of contents

  1. Front Matter
    Pages i-x
  2. Yun Xu, Changyu Hu, Yang Dai, Jie Liang
    Pages 1-35
  3. Qi Liao, Dechao Bu, Liang Sun, Haitao Luo, Yi Zhao
    Pages 51-60
  4. Masahiro Sugimoto
    Pages 61-71
  5. Raghu Chandramohan, Cheng Yang, Yunpeng Cai, May D. Wang
    Pages 73-87
  6. Sonal Kothari Phan, Ryan Hoffman, May D. Wang
    Pages 115-127
  7. Yan Yan, Xingbin Qin, Lei Wang
    Pages 129-154
  8. Gregor Schreiber, Hong Lin, Jonathan Garza, Yuntian Zhang, Minghao Yang
    Pages 155-168
  9. Chao Zhang, Shunfu Xu, Dong Xu
    Pages 169-184
  10. Fedor Lehocki, Igor Kossaczky, Martin Homola, Marek Mydliar
    Pages 185-199
  11. Chih-Wen Cheng, May D. Wang
    Pages 201-210

About this book


This book provides a comprehensive overview of different biomedical data types, including both clinical and genomic data. Thorough explanations enable readers to explore key topics ranging from electrocardiograms to Big Data health mining and EEG analysis techniques. Each chapter offers a summary of the field and a sample analysis. Also covered are telehealth infrastructure, healthcare information association rules, methods for mass spectrometry imaging, environmental biodiversity, and the global nonlinear fitness function for protein structures. Diseases are addressed in chapters on functional annotation of lncRNAs in human disease, metabolomics characterization of human diseases, disease risk factors using SNP data and Bayesian methods, and imaging informatics for diagnostic imaging marker selection.

With the exploding accumulation of Electronic Health Records (EHRs), there is an urgent need for computer-aided analysis of heterogeneous biomedical datasets. Biomedical data is notorious for its diversified scales, dimensions, and volumes, and requires interdisciplinary technologies for visual illustration and digital characterization. Various computer programs and servers have been developed for these purposes by both theoreticians and engineers. 

This book is an essential reference for investigating the tools available for analyzing heterogeneous biomedical data. It is designed for professionals, researchers, and practitioners in biomedical engineering, diagnostics, medical electronics, and related industries.


Health informatics Bioinformatics Electrocardiogram EEG Biomedical image Image fusion Electronic health record Genome Functional domain Post-translational modification Microarray High-thoughtput sequencing Information fusion Data mining Big data health mining Computational infrastructure Tele-health Metabolomics Mass spectrometry imaging OMIC

Editors and affiliations

  • Dong Xu
    • 1
  • May D. Wang
    • 2
  • Fengfeng Zhou
    • 3
  • Yunpeng Cai
    • 4
  1. 1.Digital Biology Laboratory, Computer Science DepartmentUniversity of Missouri-ColumbiaColumbiaUSA
  2. 2.Georgia Institute of Technology and Emory UniversityAtlantaUSA
  3. 3.College of Computer Science and TechnologyJilin UniversityChangchunChina
  4. 4.Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhenChina

Bibliographic information

  • DOI
  • Copyright Information Springer International Publishing Switzerland 2017
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science Computer Science (R0)
  • Print ISBN 978-3-319-44979-1
  • Online ISBN 978-3-319-44981-4
  • Series Print ISSN 2366-0988
  • Series Online ISSN 2366-0996
  • Buy this book on publisher's site