Health Informatics Data Analysis -

Health Informatics Data Analysis

Methods and Examples
Buch | Hardcover
X, 210 Seiten
2017 | 1st ed. 2017
Springer International Publishing (Verlag)
978-3-319-44979-1 (ISBN)
160,49 inkl. MwSt
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.



1 Electrocardiogram.- 2 EEG visualization and analysis techniques.- 3 Big health data mining.- 4 Computational infrastructure for tele-health.- 5 Identification and Functional Annotation of lncRNAs in human disease.- 6 Metabolomics characterization of human diseases.- 7 Metagenomics for Monitoring Environmental Biodiversity: Challenges, Progress, and Opportunities.- 8 Global nonlinearfitness function for protein structures.- 9 Clinical Assessment of Disease Risk Factors Using SNP Data and Bayesian Methods.- 10 Imaging genetics: information fusion and association techniques between biomedical images and genetic factors.

"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)

“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)

Erscheinungsdatum
Reihe/Serie Health Information Science
Zusatzinfo X, 210 p. 54 illus.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Themenwelt Mathematik / Informatik Informatik
Medizin / Pharmazie
Technik
Schlagworte Applied mathematics • Big data health mining • Bioinformatics • Biomedical image • Computational Biology/Bioinformatics • Computational infrastructure • Computer Science • Data Mining • data mining and knowledge discovery • EEG • Electrocardiogram • Electronic Health Record • Expert systems / knowledge-based systems • Functional domain • Genetics and Population Dynamics • Genome • health and safety aspects of IT • Health Informatics • High-thoughtput sequencing • image fusion • Information Fusion • Information technology: general issues • Life sciences: general issues • mass spectrometry imaging • Medical equipment and techniques • Metabolomics • microarray • OMIC • Post-translational modification • Tele-health
ISBN-10 3-319-44979-6 / 3319449796
ISBN-13 978-3-319-44979-1 / 9783319449791
Zustand Neuware
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