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 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.

Focuses on novel statistical methods to address new biomedical challenges Presents the necessary mathematical rigour with an approachable writing style Describes open source code so readers can reproduce the statistical methods in the clinic

Autorentext

Yolanda Larriba is an Assistant Professor at the Department of Statistics and Operations Research of the University of Valladolid (Spain). Her research mainly concerns the development of statistical methodologies in the field of order restricted inference with applications to medical science.

Inhalt
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.