Results 51 to 60 of about 988,211 (198)
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 +13 more
wiley +1 more source
Correlation-based spike sorting of multivariate data
Automated classification of waveforms is an important method of data processing used in various fields of science, such as neuroscience, biomedical engineering, etc. This work shows the possibility of sorting special waveforms i.e.
Larionov Pavel +2 more
doaj +1 more source
ABSTRACT Objectives Focal cortical dysplasia (FCD) is the most common etiology of drug‐resistant epilepsy in children. Focal to bilateral tonic–clonic seizures (FBTCS) mark a high risk of drug‐resistant epilepsy and involve thalamocortical circuitry in their generation and propagation.
Hua Xie +8 more
wiley +1 more source
ABSTRACT Objective Early risk stratification may support clinical decision‐making in spontaneous intracerebral hemorrhage (ICH). We aimed to develop and internally validate HAGIV, a score integrating frequency of imaging markers (FIM), a time‐adjusted non‐contrast computed tomography (CT) metric of hematoma expansion, with established predictors for 90‐
Lei Song +10 more
wiley +1 more source
Generalized Point Estimators for Fuzzy Multivariate Data
Data analysis methods are necessary tools in evaluating and better understanding the information of interest. However, there are limitations in applying standard statistical methods to specific data analyses.
Owat Sunanta
doaj +1 more source
ABSTRACT Objective The prognosis of glioblastoma (GBM) remains highly unfavorable, largely due to high tumor heterogeneity and an immunosuppressive microenvironment. However, the functional role of PANoptosis in this context is poorly understood. Methods Patients were stratified via K‐means clustering. A risk score model was constructed using prognosis‐
Langfei Tian +6 more
wiley +1 more source
Multivariate stochastic volatility modeling of neural data
Because multivariate autoregressive models have failed to adequately account for the complexity of neural signals, researchers have predominantly relied on non-parametric methods when studying the relations between brain and behavior.
Tung D Phan +3 more
doaj +1 more source
ABSTRACT Objective To determine whether discontinuing anti‐CD20 therapy in people with relapsing‐onset MS aged over 50 is associated with an increased risk of relapse, inflammatory activity, confirmed disability accrual, and serious infection compared with continuing therapy.
Alexia Moukhine +40 more
wiley +1 more source
Data De-Noise for Multivariate T2 and S-Charts Using Multivariate Wavelets
In this research, proposed multivariate charts were created corresponding to T2 and S-charts that are robust to noise data by using multivariate wavelet shrinkage, that dealt with the contamination problem before constructing Shewhart charts, through ...
Dler Hussein Kadir +3 more
doaj +1 more source
Probabilistic Encoding Models for Multivariate Neural Data
A key problem in systems neuroscience is to characterize how populations of neurons encode information in their patterns of activity. An understanding of the encoding process is essential both for gaining insight into the origins of perception and for ...
Marcus A. Triplett, Geoffrey J. Goodhill
doaj +1 more source

