Results 101 to 110 of about 1,813,028 (298)
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective We aim to comprehensively analyze how regional tumor and edema characteristics are associated with clinical presentations and survival outcomes in a large cohort of glioblastoma patients. Methods Patients with IDH‐wildtype glioblastoma who received brain MRI from 2010 to 2023 were included.
Daniel J. Zhou +16 more
wiley +1 more source
Automatic Face Recognition Based on Sparse Representation and Extended Transfer Learning
IEEE Access, 2019 Sparse representation has exhibited excellent performance in face recognition. However, this method requires some areas for improvement, especially on insufficient face samples.
Zhi Liu +5 more
doaj +1 more source
Uncovering G Protein‐Coupled Receptors: Novel Targets and Biomarkers for Predicting Glioma Prognosis
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Low‐grade gliomas (LGG) exhibit significant heterogeneity and recurrence risk. G protein‐coupled receptors (GPCR) contribute to glioma malignant progression, but their prognostic value remains unclear. This work attempts to formulate a GPCR‐based outcome‐predicting model for LGG. Methods Based on TCGA LGG data, the enrichment scores
Jun Yang +4 more
wiley +1 more source
Improved sparse representation method for image classification
IET Computer Vision, 2017 Among all image representation and classification methods, sparse representation has proven to be an extremely powerful tool. However, a limited number of training samples are an unavoidable problem for sparse representation methods.
Shigang Liu +4 more
doaj +1 more source
Group Sparse Representation Based Dictionary Learning for SAR Image Despeckling
IEEE Access, 2019 Since the sparse representation coefficients of synthetic aperture radar (SAR) images often appear in clusters with intrinsic structure, traditional sparse representation theory cannot capture this property.
Su Liu, Gong Zhang, Wenbo Liu
doaj +1 more source
Annals of Clinical and Translational Neurology, EarlyView.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
Arthritis Care &Research, EarlyView.Objective We aimed to estimate the prevalence and cumulative incidence of hydroxychloroquine retinopathy (HCQ‐R) and its risk factors among patients receiving long‐term HCQ with rheumatic diseases through a systematic review and meta‐analysis of observational studies that used spectral‐domain optical coherence tomography (SD‐OCT) for screening ...
Narsis Daftarian +4 more
wiley +1 more source
Monte Carlo methods for adaptive sparse approximations of time-series
, 2007 This paper deals with adaptive sparse approximations of time-series. The work is based on a Bayesian specification of the shift-invariant sparse coding model.
Michael E. Davies +3 more
core +1 more source
, 2022 Dynamic graph neural networks (DGNNs) have been widely used in modeling and representation learning of graph structure data. Current dynamic representation learning focuses on either discrete learning which results in temporal information loss, or ...
Liu, Chao +15 more
core +1 more source
Arthritis Care &Research, EarlyView.Objective This research article aims to describe the prevalence, associations, and health‐related quality of life (HRQoL) impact of mucocutaneous features of systemic lupus erythematosus (SLE). Methods Data from the Asia‐Pacific Lupus Collaboration cohort were analyzed (2013–2021).
Amanda M. Saracino +42 more
wiley +1 more source