Results 81 to 90 of about 5,191,119 (260)
A simultaneous confidence band provides useful information on the plausible range of the unknown regression model. Construction of a simultaneous confidence band has a history going back to Working and Hotelling (1929) and is often a hard problem when ...
Liu, Wei, Liu, W., Lin, S., Lin, Shan
core +1 more source
ABSTRACT Objective Down syndrome regression disorder is a syndrome characterized by subacute loss of cognitive, behavioral, and functional abilities in individuals with Down syndrome. Electroencephalography abnormalities are frequently observed during evaluation, but it remains unclear whether these findings represent a dynamic marker of disease ...
Jonathan D. Santoro +14 more
wiley +1 more source
A spiking neural network implementation of Gaussian belief propagation
Bayesian inference offers a principled account of information processing in natural agents. However, it remains an open question how neural mechanisms perform their abstract operations.
Sepideh Adamiat +2 more
doaj +1 more source
T1 Over Squared Proton Density Ratio to Characterize Multiple Sclerosis Lesions
ABSTRACT Objective Differentiating remyelinated from demyelinated lesions in MS remains challenging without histological confirmation. This study introduces the T1‐to‐PD2 ratio (TPR) imaging approach and evaluates its ability to characterize MS lesions alongside other quantitative MRI (qMRI) metrics. Methods Thirty individuals with MS (mean age: 47.5 ±
Sarah J. Wright +10 more
wiley +1 more source
ABSTRACT Background Factors associated with relapse course and disability in myelin oligodendrocyte glycoprotein antibody‐associated disease (MOGAD) remain incompletely understood. Objectives To identify clinical and modifiable factors associated with relapse and disability in MOGAD. Methods In this ambispective multicentre cohort study using data from
Yingtao Wang +23 more
wiley +1 more source
Inference for high-dimensional sparse econometric models [PDF]
This article is about estimation and inference methods for high dimensional sparse (HDS) regression models in econometrics. High dimensional sparse models arise in situations where many regressors (or series terms) are available and the regression ...
Christian Hansen +2 more
core
ABSTRACT Objective To evaluate the expression of nine blood RNA biomarkers in a clinical trial based on genes previously identified in an experimental monkey model of stroke for diagnosis feasibility and prognostication. Methods IBIS‐CT1 was a prospective longitudinal study enrolling patients with ischemic stroke (IS) or intracerebral hemorrhage (ICH ...
Salomé Retailleau +11 more
wiley +1 more source
Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders
ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif +17 more
wiley +1 more source
Multivariate Student -t Regression Models: Pitfalls and Inference [PDF]
We consider likelihood-based inference from multivariate regression models with independent Student-t errors. Some very intruiging pitfalls of both Bayesian and classical methods on the basis of point observations are uncovered. Bayesian inference may be
Steel, M.F.J., Fernández, C.
core
ABSTRACT Objective Treatment of disorders of consciousness (DoC) remains a major clinical challenge, and noninvasive, targeted modulation of deep brain structures has emerged as a promising therapeutic strategy. We aimed to evaluate the feasibility/safety and preliminary effects of thalamic temporal interference stimulation (TIS) targeting centromedian‐
Gengyao Hu +7 more
wiley +1 more source

