Neurointervention is a highly specialized area of medicine and, as such, neurointerventional research studies are often more challenging to conduct, require large, multicenter efforts and longer study ...

In microbiome studies, addressing the unique characteristics of sequence data—such as compositionality, zero inflation, overdispersion, high dimensionality, and non-normality—is crucial for accurate ...

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision ...

Interpretability has drawn increasing attention in machine learning. Partially linear additive models provide an attractive middle ground between the simplicity of generalized linear model and the ...

In data analysis, time series forecasting relies on various machine learning algorithms, each with its own strengths. However, we will talk about two of the most used ones. Long Short-Term Memory ...

A python package for penalized generalized linear models that supports fitting and model selection for structured, adaptive and non-convex penalties.

Introduction to Generalized Linear Models In this two day course, we provide a comprehensive practical and theoretical introduction to generalized linear models using R. Generalized linear models are ...

Abstract: Inferring neuron network construction, the ideal situation is to explore the relationship between synaptic and functional connection. In this paper, we apply the general linear model(GLM) to ...