Titlebook: Statistical Methods at the Forefront of Biomedical Advances; Yolanda Larriba Book 2023 The Editor(s) (if applicable) and The Author(s), un

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iting style.Describes open source code so readers can reprod.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 mathe

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, 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..978-3-031-32731-5978-3-031-32729-2

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Machine Learning Applied to Omics Data, apply the reviewed methods to a real data set from TCGA made of 107 tumoral pancreatic samples and 117,486 germline SNPs, showing the good performance of the proposed methods to predict the immunological infiltration in pancreatic cancer.

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Hippocampus Shape Analysis via Skeletal Models and Kernel Smoothing, density ridges for data on the polysphere and involves addressing high-dimensional computational challenges. For the analyzed dataset, our model-free indexing of shape variability reveals that the spokes defining the sharpness of the elongated extremes of hippocampi concentrate the most variation among subjects.

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Application of Quantile Regression Models for Biomedical Data,t statistic will be shown. Furthermore, in order to approximate the critical values of the test, a bootstrap mechanism is used, which is similar to the proposal developed in [.]. In addition, an extensive simulation study and an interesting real data application will be presented in order to show the behaviour of the new test in practice.

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