Results 151 to 160 of about 9,847,764 (300)
White Matter and Perivascular Imaging Changes in Alzheimer's Disease and Cerebral Amyloid Angiopathy
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Peak‐width of skeletonized mean diffusivity (PSMD) and diffusion tensor imaging–analysis along the perivascular space (DTI‐ALPS), reflecting white matter integrity and glymphatic function, are altered in Alzheimer's disease (AD).
Debina Laishram +3 more
wiley +1 more source
Renmin ZhujiangStudying extreme climate change is of paramount significance for safeguarding China's national security and promoting sustainable socioeconomic development.
JIA Yizhou +4 more
doaj +2 more sources
Association Between Neurofilament Light Chain and Real‐World Ambulatory Function in Progressive MS
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Neurofilament light chain (NfL) is a biomarker of neuroaxonal injury in multiple sclerosis (MS), yet associations with functional outcomes remain unclear. Longitudinal associations between serum NfL (sNfL) and daily step count (STEPS) from wearable devices were assessed in a large international progressive MS cohort.
Gabby B. Joseph +5 more
wiley +1 more source
Extreme risk in Asian equity markets [PDF]
Extreme price movements associated with tail returns are catastrophic for all investors and it is necessary to make accurate predictions of the severity of these events.
Cotter, John
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To identify inflammatory analytes in cerebrospinal fluid (CSF) and plasma associated with cognitive decline in cognitively normal (CN) older adults at risk for Alzheimer's disease (AD). Methods In a longitudinal study of 118 CN older adults (65–80 years, 54% APOE ε4, 26% preclinical AD), 1331 CSF and 1501 plasma analytes were ...
Jagan A. Pillai +13 more
wiley +1 more source
Bayesian Extreme Value Mixture Modelling for Estimating VaR [PDF]
A new extreme value mixture modelling approach for estimating Value-at-Risk (VaR) is proposed, overcoming the key issues of determining the threshold which defines the distribution tail and accounts for uncertainty due to threshold choice.
Les Oxley +3 more
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Autoimmune glial fibrillary acidic protein astrocytopathy (GFAP‐A) is an inflammatory central nervous system disorder with variable outcomes. Relapse occurs in a subset of patients, but early predictors remain unclear. We aimed to identify admission‐available features associated with 1‐year recurrence and develop an interpretable ...
Qingting Hong +10 more
wiley +1 more source
Are realized volatility models good candidates for alternative Value at Risk prediction strategies? [PDF]
In this paper, we assess the Value at Risk (VaR) prediction accuracy and efficiency of six ARCH-type models, six realized volatility models and two GARCH models augmented with realized volatility regressors.
Refenes, Apostolos P. +2 more
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Arthritis Care &Research, EarlyView.Objective The objective of this study was to estimate the minimal important change (MIC) and minimal clinically important difference (MCID) for pain and physical function in individuals with hip osteoarthritis (OA) following a physiotherapist‐guided exercise intervention.
Yareni Guerrero +8 more
wiley +1 more source
Generalized Extreme Value Regression for Binary Rare Events Data: an Application to Credit Defaults [PDF]
The most used regression model with binary dependent variable is the logistic regression model. When the dependent variable represents a rare event, the logistic regression model shows relevant drawbacks.
Silvia Angela Osmetti +1 more
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