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.
