Results 51 to 60 of about 253,016 (276)
Remote Assessment of Ataxia Severity in SCA3 Across Multiple Centers and Time Points
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Spinocerebellar ataxia type 3 (SCA3) is a genetically defined ataxia. The Scale for Assessment and Rating of Ataxia (SARA) is a clinician‐reported outcome that measures ataxia severity at a single time point. In its standard application, SARA fails to capture short‐term fluctuations, limiting its sensitivity in trials.
Marcus Grobe‐Einsler +20 more
wiley +1 more source
Applied and Environmental MicrobiologyThe spaceflight environment imparts unique selective pressures on the plants and microbes of plant growth chambers on the International Space Station (ISS), which generally manifests through genetic signatures associated with a heightened response to ...
Anya Volter +8 more
doaj +1 more source
Adaptive robust variable selection
, 2014 Heavy-tailed high-dimensional data are commonly encountered in various scientific fields and pose great challenges to modern statistical analysis. A natural procedure to address this problem is to use penalized quantile regression with weighted $L_1 ...
Barut, Emre +2 more
core +1 more source
Impact of Asymptomatic Intracranial Hemorrhage on Outcome After Endovascular Stroke Treatment
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Endovascular treatment (EVT) achieves high rates of recanalization in acute large‐vessel occlusion (LVO) stroke, but functional recovery remains heterogeneous. While symptomatic intracranial hemorrhage (sICH) has been well studied, the prognostic impact of asymptomatic intracranial hemorrhage (aICH) after EVT is less certain ...
Shihai Yang +22 more
wiley +1 more source
Don't Fall for Tuning Parameters: Tuning-Free Variable Selection in High Dimensions With the TREX
, 2015 Lasso is a seminal contribution to high-dimensional statistics, but it hinges on a tuning parameter that is difficult to calibrate in practice. A partial remedy for this problem is Square-Root Lasso, because it inherently calibrates to the noise variance.
Lederer, Johannes, Müller, Christian
core +1 more source
Value of MRI Outcomes for Preventive and Early‐Stage Trials in Spinocerebellar Ataxias 1 and 3
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To examine the value of MRI outcomes as endpoints for preventive and early‐stage trials of two polyglutamine spinocerebellar ataxias (SCAs). Methods A cohort of 100 participants (23 SCA1, 63 SCA3, median Scale for the Assessment and Rating of Ataxia (SARA) score = 5, 42% preataxic, and 14 gene‐negative controls) was scanned at 3T up ...
Thiago J. R. Rezende +26 more
wiley +1 more source
A Nonlinear Deep Learning Model for Oxygen Content of Flue Gas
Journal of Harbin University of Science and Technology, 2020 It is a deviation reality that lifespan of some products is described by common distributions. However，the ZZ distribution can better describe the lifespan distribution of this type of product.
TANG Zhenhao, LI Yanyan, CAO Shengxian
doaj +1 more source
Frontiers in Neuroscience, 2023 Motor imagery (MI) electroencephalogram (EEG) signals have a low signal-to-noise ratio, which brings challenges in feature extraction and feature selection with high classification accuracy.
Manqing Wang +7 more
doaj +1 more source
Transductive versions of the LASSO and the Dantzig Selector [PDF]
, 2009 We consider the linear regression problem, where the number $p$ of covariates is possibly larger than the number $n$ of observations $(x_{i},y_{i})_{i\leq i \leq n}$, under sparsity assumptions.
Alquier, Pierre, Hebiri, Mohamed
core +5 more sources
The log-linear group-lasso estimator and its asymptotic properties
, 2011 We define the group-lasso estimator for the natural parameters of the exponential families of distributions representing hierarchical log-linear models under multinomial sampling scheme.
Nardi, Yuval, Rinaldo, Alessandro
core +2 more sources