Results 91 to 100 of about 1,871,059 (300)

A deep semantic analysis based on sparse feature fusion and knowledge distillation in urban planning

Array
To comprehensively analyze the deep semantic meaning, morphology, and attributes of targets across various scenarios and conditions, this study explores sparse feature fusion and knowledge distillation techniques in deep semantic analysis.
Yuan Li, Yutong Wang, Qi Shen
doaj   +1 more source

Understanding and Mitigating the Risk of Accelerated Biological Aging in Survivors of Cancer: A Scoping Review

Aging and Cancer, EarlyView.
Cancer treatment is associated with measurable acceleration of biological aging across epigenetic, telomere, senescence, and immune biomarkers. However, biomarker validation and interventional strategies remain limited, especially in hematologic malignancies, underscoring the need for standardized multi‐omic aging assessments and adequately powered ...
Moataz Ellithi, Emily Herdman, Danielle Westmark, Vijaya R. Bhatt   +3 more
wiley   +1 more source

SAR Target Configuration Recognition via Product Sparse Representation

Sensors, 2018
Sparse representation (SR) has been verified to be an effective tool for pattern recognition. Considering the multiplicative speckle noise in synthetic aperture radar (SAR) images, a product sparse representation (PSR) algorithm is proposed to achieve ...
Ming Liu, Shichao Chen, Fugang Lu, Mengdao Xing   +3 more
doaj   +1 more source

Risk of Non‐Arteritic Anterior Ischemic Optic Neuropathy in Idiopathic Intracranial Hypertension Patients Treated with GLP‐1 Receptor Agonists

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Introduction Glucagon‐like peptide‐1 receptor agonists (GLP‐1 RAs) have demonstrated significant weight‐reducing effects and may offer benefits in idiopathic intracranial hypertension (IIH); however, recent concerns about the risk of non‐arteritic anterior ischemic optic neuropathy (NAION) have emerged.
Faisal A. Al‐Harbi, Mohanad A. Alkuwaiti, Yazeed B. Alaql, Ahmed K. Alsaif, Ahmed A. Alessa, Meshari Ayed Alharbi, Mohammed Alfalah, Saud A. Alnaaim, Sajjad M. AlHaddad, Ahmed Y. Azzam   +9 more
wiley   +1 more source

Spatial and Volumetric Characteristics of Glioblastoma: Associations With Clinical Presentation and Survival

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, Marc Jaskir, Julian Gal, Yombe Fonkeu, Christos Davatzikos, MacLean P. Nasrallah, Jose Garcia, Rubo Xing, Stephen J. Bagley, Arati Desai, Richard E. Phillips, Steven Tobochnik, Colin A. Ellis, James J. Gugger, Nishant Sinha, Joel M. Stein, Kathryn A. Davis   +16 more
wiley   +1 more source

Sparse Representation for Cyclotomic Fields [PDF]

Experimental Mathematics, 2007
Currently, all major implementations of cyclotomic fields as well as number fields are based on a dense model in which elements are represented either as dense polynomials in the generator of the field or as coefficient vectors with respect to a fixed basis. While this representation allows for the asymptotically fastest arithmetic for general elements,
openaire   +2 more sources

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, Dongxu Zhang, Dongyuan Liu, Da Lin, Hao Wang   +4 more
wiley   +1 more source

Semantic Sparse Representation of Disease Patterns [PDF]

, 2010
Semantic Sparse Representation of Disease PatternsSparse data representation is discussed in a context of useful fundamentals led to semantic content description and extraction of information.
Przelaskowski, A., Artur Przelaskowski
core   +1 more source

Electroencephalographic Normalization as a Biomarker of Clinical Recovery in Down Syndrome Regression Disorder

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, Mackenzie Silverman, Maeve C. Lucas, Mariam M. Yousuf, Samuel T. Otey, Stella V. Gray, Brittany Jordan, Madeline D. Kahan, Latanya D. Agurs, Michelle Van Hirtum Das, Deborah Holder, Devin King, Eileen A. Quinn, Ryan Kammeyer, Michael S. Rafii   +14 more
wiley   +1 more source

Image fusion method based on simultaneous sparse representation with non‐subsampled contourlet transform

IET Computer Vision, 2019
The image fusion method based on sparse representation in the single‐scale image domain has produced better fusion results than the classic methods based on multi‐scale analysis nowadays.
Guiqing He, Siyuan Xing, Xingjian He, Jun Wang, Jianping Fan   +4 more
doaj   +1 more source