Results 201 to 210 of about 687,122 (255)

Subclinical Optic Nerve Involvement in Radiologically Isolated Syndrome: Multimodal Detection and Diagnostic Impact

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives We aimed to determine the frequency of subclinical optic nerve (ON) lesions using MRI, optical coherence tomography (OCT), and visual evoked potentials (VEP) in radiologically isolated syndrome (RIS), and to assess their diagnostic and prognostic significance.
Christine Lebrun‐Frenay, Cassandre Landes‐Château, Lydiane Mondot, Mikael Cohen, Margherita Popolo, Jérôme de Seze, Bertrand Bourre, Françoise Durand‐Dubief, Olivier Casez, Orhun H. Kantarci, Aksel Siva, Stephanie Baillif, Darin T. Okuda, Letizia Leocani   +13 more
wiley   +1 more source

Neurochemical Endpoints to Inform Early‐Stage Trials of Spinocerebellar Ataxia 2 and 3 in a Multisite Setting

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Neurochemical levels measured by brain MR spectroscopy (MRS) have been proposed as endpoints for clinical trials in early‐stage spinocerebellar ataxia (SCA) trials. We tested their trial‐readiness by quantifying neurochemicals in three affected brain regions in early‐stage cohorts of SCA2 and SCA3, examining their reproducibility in ...
James M. Joers, Yaqiao Wei, Dinesh K. Deelchand, Adam Berrington, Young Woo Park, Guita Banan, Michal Povazan, Jens T. Rosenberg, André J. W. van der Kouwe, Tetsuo Ashizawa, Khalaf O. Bushara, Chiadi U. Onyike, Sub H. Subramony, Jeremy D. Schmahmann, Brian J. Soher, Peter B. Barker, Thomas H. Mareci, Eva‐Maria Ratai, Lynn E. Eberly, Gülin Öz   +19 more
wiley   +1 more source

T1 Over Squared Proton Density Ratio to Characterize Multiple Sclerosis Lesions

Annals of Clinical and Translational Neurology, EarlyView.
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, Scotty G. McKay, Jean Ramos Bou, Fen Bao, Vivian B. Truong, Chenyang Li, Li Jiang, Anza B. Memon, E. Mark Haacke, Yulin Ge, Yongsheng Chen   +10 more
wiley   +1 more source

Model Uncertainty, State Uncertainty, and State-Space Models [PDF]

SSRN Electronic Journal, 2012
State-space models have been increasingly used to study macroeconomic and financial problems. A state-space representation consists of two equations, a measurement equation which links the observed variables to unobserved state variables and a transition equation describing the dynamics of the state variables.
Young, ER, Luo, Y, Nie, J
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Benchmarking by State Space Models

International Statistical Review / Revue Internationale de Statistique, 1997
SummaryWe have a monthly series of observations which are obtained from sample surveys and are therefore subject to survey errors. We also have a series of annual values, called benchmarks, which are either exact or are substantially more accurate than the survey observations; these can be either annual totals or accurate values of the underlying ...
Durbin, J., Quenneville, B.
openaire   +2 more sources

State-Space Models

2010
A very general model that subsumes a whole class of special cases of interest in much the same way that linear regression does is the state-space model or the dynamic linear model, which was introduced in Kalman [112] and Kalman and Bucy [113]. The model arose in the space tracking setting, where the state equation defines the motion equations for the ...
Robert H. Shumway, David S. Stoffer
openaire   +1 more source

State Space Models

2021
This chapter introduces state space models and provides some motivating examples. Linear Gaussian and non-linear, non-Gaussian models are introduced. Examples include linear trend and seasonal time series, time-varying regression, bearings-only tracking, financial time series and systems identification state space models. The chapter sets the stage for
Christiaan Heij, André C.M. Ran, Frederik van Schagen   +2 more
openaire   +2 more sources

state space models

2008
State space models is a rather loose term given to time series models, usually formulated in terms of unobserved components, that make use of the state space form for their statistical treatment.
openaire   +1 more source