04770nam a22005895i 4500 978-3-319-44981-4 DE-He213 20210617092701.0 cr nn 008mamaa 170909s2017 gw | s |||| 0|eng d 9783319449814 978-3-319-44981-4 10.1007/978-3-319-44981-4 doi R858-R859.7 UBH bicssc MED000000 bisacsh UBH thema 502.85 23 Health Informatics Data Analysis [electronic resource] : Methods and Examples / edited by Dong Xu, May D. Wang, Fengfeng Zhou, Yunpeng Cai. 1st ed. 2017. Cham : Springer International Publishing : Imprint: Springer, 2017. X, 210 p. 54 illus. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Health Information Science, 2366-0988 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. 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. Data mining. Bioinformatics. Biomathematics. Health Informatics. https://scigraph.springernature.com/ontologies/product-market-codes/I23060 Health Informatics. https://scigraph.springernature.com/ontologies/product-market-codes/H28009 Data Mining and Knowledge Discovery. https://scigraph.springernature.com/ontologies/product-market-codes/I18030 Computational Biology/Bioinformatics. https://scigraph.springernature.com/ontologies/product-market-codes/I23050 Genetics and Population Dynamics. https://scigraph.springernature.com/ontologies/product-market-codes/M31010 Xu, Dong. editor. edt http://id.loc.gov/vocabulary/relators/edt Wang, May D. editor. edt http://id.loc.gov/vocabulary/relators/edt Zhou, Fengfeng. editor. edt http://id.loc.gov/vocabulary/relators/edt Cai, Yunpeng. editor. edt http://id.loc.gov/vocabulary/relators/edt SpringerLink (Online service) Springer Nature eBook Printed edition: 9783319449791 Printed edition: 9783319449807 Printed edition: 9783319831787 Health Information Science, 2366-0988 https://doi.org/10.1007/978-3-319-44981-4 ZDB-2-SCS ZDB-2-SXCS Computer Science (SpringerNature-11645) Computer Science (R0) (SpringerNature-43710)