Overview
- Offers a comprehensive overview of biomedical data types and explains why and how to examine types of data
- Chapters provide both field overviews and sample analysis
- Examines OMICs, an increasingly critical part of health informatics with official FDA recognition and a wide range of diagnosis applications
- Includes supplementary material: sn.pub/extras
Part of the book series: Health Information Science (HIS)
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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.
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.
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Keywords
- 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
Table of contents (13 chapters)
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Front Matter
Reviews
“It would be nice to enhance the examples presented throughout the book with a more detailed step-by-step guide for non-experts in the medical domain, including a reader-friendly analysis and interpretation of the results obtained along with a summary of lessons learned.” (Sergio Ilarri, Computing Reviews, April, 2018)
Editors and Affiliations
Bibliographic Information
Book Title: Health Informatics Data Analysis
Book Subtitle: Methods and Examples
Editors: Dong Xu, May D. Wang, Fengfeng Zhou, Yunpeng Cai
Series Title: Health Information Science
DOI: https://doi.org/10.1007/978-3-319-44981-4
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing Switzerland 2017
Hardcover ISBN: 978-3-319-44979-1Published: 18 September 2017
Softcover ISBN: 978-3-319-83178-7Published: 10 August 2018
eBook ISBN: 978-3-319-44981-4Published: 08 September 2017
Series ISSN: 2366-0988
Series E-ISSN: 2366-0996
Edition Number: 1
Number of Pages: X, 210
Number of Illustrations: 54 b/w illustrations
Topics: Health Informatics, Health Informatics, Data Mining and Knowledge Discovery, Computational Biology/Bioinformatics, Genetics and Population Dynamics