Statistical Methods at the Forefront of Biomedical Advances

This book presents novel statistics methods and reproducible software that helps to solve challenging problems in biomedicine. Specifically, it consists of a collection of 11 chapters contributed by some of the leading experts in the mathematical and statistical field which address new challenges in...

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Autor corporatiu: SpringerLink (Online service)
Altres autors: Larriba, Yolanda (Editor)
Format: Electrònic eBook
Idioma:anglès
Publicat: Cham : Springer International Publishing : Imprint: Springer, 2023.
Edició:1st ed. 2023.
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Accés en línia:https://doi.org/10.1007/978-3-031-32729-2
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505 0 |a Forecasting of SARS-COV-2 dynamic: beyond the classical SIR model -- Derivation of OED methods for applications in cytogenetic biodosimetry -- Minimum Phi-divergence tests for ophthalmological data grouped in clusters -- Multimodality test for determining which genes distinguish oncological patients -- Exploring the relationship between different cancer sites using disease mapping models -- Advances in flow cytometry gating based on distances and divergences in probability spaces -- Application of quantile regression models for biomedical data -- Hippocampus shape analysis via skeletal models and kernel smoothing -- Methods for analysis of microbiome count data with applications -- The FMM model as a classifier of cardiovascular pathologies -- A novel statistical insight of the circadian markers that govern cardiac rhythms -- Sleep and circadian synchronization assessment from multivariate recordings. . 
520 |a This book presents novel statistics methods and reproducible software that helps to solve challenging problems in biomedicine. Specifically, it consists of a collection of 11 chapters contributed by some of the leading experts in the mathematical and statistical field which address new challenges in very disparate biomedical areas, such as genomics, cancer, circadian biology, microbiome, mental disorders, and more. The mathematical rigor is written in a user-friendly way to serve a general biomedical audience ranging from trainees or students to doctors, as well as scientific researchers, university departments, and PhD students. 
532 8 |a Accessibility summary: This PDF does not fully comply with PDF/UA standards, but does feature limited screen reader support, described non-text content (images, graphs), bookmarks for easy navigation and searchable, selectable text. Users of assistive technologies may experience difficulty navigating or interpreting content in this document. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. 
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650 0 |a Biometry. 
650 0 |a Biomedical engineering. 
650 0 |a Bioinformatics. 
650 0 |a Biological models. 
650 1 4 |a Biostatistics. 
650 2 4 |a Biomedical Engineering and Bioengineering. 
650 2 4 |a Computational and Systems Biology. 
650 2 4 |a Biological Models. 
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