TY  - BOOK
AU  - Larriba,Yolanda
ED  - SpringerLink (Online service)
TI  - Statistical Methods at the Forefront of Biomedical Advances
SN  - 9783031327292
AV  - QH323.5 
U1  - 570.15195 23
PY  - 2023///
CY  - Cham
PB  - Springer International Publishing, Imprint: Springer
KW  - Biometry
KW  - Biomedical engineering
KW  - Bioinformatics
KW  - Biological models
KW  - Biostatistics
KW  - Biomedical Engineering and Bioengineering
KW  - Computational and Systems Biology
KW  - Biological Models
N1  - Acceso multiusuario; 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.
N2  - 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
UR  - http://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-3-031-32729-2
ER  -