Results 21 to 30 of about 2,991,648 (129)
Journal of Medical Radiation Sciences, Volume 73, Issue 3, Page 250-258, September 2026.This study evaluated four stereotactic radiosurgery planning approaches for posterior choroidal melanoma (CM). Analysis of thirteen CM cases resulted in a clinically meaningful reduction in dose to the brain for Brainlab Elements modulated arcs (BE) and Varian Eclipse HyperArc modulated arcs (HA) compared to Brainlab iPlan dynamic conformal arc therapy
Robert Nigro +5 more
wiley +1 more source
Non‐Elliptical Dimension Reduction in Survival Regression
Stat, Volume 15, Issue 3, September 2026.ABSTRACT Sufficient dimension reduction (SDR) in survival regression aims to identify low‐dimensional structures that preserve the relationship between survival time and predictors. Classical SDR methods, such as sliced inverse regression (SIR), rely on strong assumptions such as linearity, constant variance and coverage conditions, which are often ...
Minjee Kim, Minjeong Kim, Jae Keun Yoo
wiley +1 more source
Student Sliced Inverse Regression [PDF]
, 2016 International audienceSliced Inverse Regression (SIR) has been extensively used to reduce the dimension of the predictor space before performing regression. SIR is originally a model free method but it has been shown to actually correspond to the maximum
Chiancone, Alessandro +2 more
core +1 more source
Exploring the Sensitivity Limits of Neuronal Current Imaging With MRI and MEG in the Human Brain
Human Brain Mapping, Volume 47, Issue 11, 01 August 2026.Combined spin‐lock fMRI, MEG, BOLD‐fMRI, and phantom experiments reveal that physiological neuronal magnetic fields lie below the in vivo detection threshold of the current spin‐lock implementations at 3T, defining quantitative sensitivity limits for MR‐based neuronal current imaging. ABSTRACT Conventional BOLD‐fMRI relies on hemodynamic responses that
Milena Capiglioni +5 more
wiley +1 more source
Penalized single-index quantile regression [PDF]
, 2013 This article is made available through the Brunel Open Access Publishing Fund. Copyright for this article is retained by the author(s), with first publication rights granted to the journal.
Yu, K
core +1 more source
On Metric Choice in Dimension Reduction for Fréchet Regression
International Statistical Review, Volume 94, Issue 2, Page 325-346, August 2026.Summary Fréchet regression is becoming a mainstay in modern data analysis for analysing non‐traditional data types belonging to general metric spaces. This novel regression method is especially useful in the analysis of complex health data such as continuous monitoring and imaging data.
Abdul‐Nasah Soale +3 more
wiley +1 more source
Comparison of sliced inverse regression approaches for underdetermined cases [PDF]
, 2014 International audienceAmong methods to analyze high-dimensional data, the sliced inverse regression (SIR) is of particular interest for non-linear relations between the dependent variable and some indices of the covariate.
Coudret, Raphaël +2 more
core +4 more sources
On the regularization of Sliced Inverse Regression
, 2010 International audienceSliced Inverse Regression (SIR) is an effective method for dimension reduction in high dimensional regression problems. The original method, however, requires the inversion of the predictors covariance matrix.
Girard, Stéphane
core +1 more source
JOR SPINE, Volume 9, Issue 2, June 2026.Final multiple linear regression model: heat maps showing Bone‐specific Physical Activity Questionnaire score associations with T2 values in five intervertebral disc (IVD) regions with statistically significant covariates controlled for at individual spinal levels.
Claire L. Samanna +12 more
wiley +1 more source
On the Foundational Arguments of Sufficient Dimension Reduction
WIREs Computational Statistics, Volume 18, Issue 2, June 2026.Contemporary Sufficient Dimension Reduction, a versatile method for extracting material information from data, can serve as a preprocessor for classical modeling and inference, or as a standalone theory that leads directly to statistical inference. ABSTRACT Sufficient dimension reduction (SDR) refers to supervised methods of dimension reduction that ...
R. Dennis Cook
wiley +1 more source