Results 241 to 250 of about 6,797,677 (284)
Incorporating topical stance into signed bipartite networks for user retweet prediction. [PDF]
Li L, Chen Z, Ye H, Zhang Y.
europepmc +1 more source
Whole‐Body Pattern of Muscle Degeneration and Progression in Sarcoglycanopathies
ABSTRACT Objective To characterize whole‐body intramuscular fat distribution pattern in patients with sarcoglycanopathies and explore correlations with disease severity, duration and age at onset. Methods Retrospective, cross‐sectional, multicentric study enrolling patients with variants in one of the four sarcoglycan genes who underwent whole‐body ...
Laura Costa‐Comellas +39 more
wiley +1 more source
Orbitofrontal Thickness and Network Associations as Transdiagnostic Signature of Amotivation Along the Bipolar-Schizophrenia Spectrum. [PDF]
Franz M +17 more
europepmc +1 more source
ABSTRACT Objective To investigate the value of constructing models based on habitat radiomics and pathomics for predicting the risk of progression in high‐grade gliomas. Methods This study conducted a retrospective analysis of preoperative magnetic resonance (MR) images and pathological sections from 72 patients diagnosed with high‐grade gliomas (52 ...
Yuchen Zhu +14 more
wiley +1 more source
Social support, social networks, and mental health of six refugee subgroups in Arizona: Findings from a pilot study. [PDF]
Um MY +9 more
europepmc +1 more source
ABSTRACT Objective Glioma recurrence severely impacts patient prognosis, with current treatments showing limited efficacy. Traditional methods struggle to analyze recurrence mechanisms due to challenges in assessing tumor heterogeneity, spatial dynamics, and gene networks.
Lei Qiu +10 more
wiley +1 more source
Autapses enable temporal pattern recognition in spiking neural networks. [PDF]
Yaqoob M, Steuber V, Wróbel B.
europepmc +1 more source
Quantifying the stability landscapes of psychological networks. [PDF]
Cui J +4 more
europepmc +1 more source
Inference of Genetic Networks from Pseudo Time Series of Single-cell Gene Expression Data using Modified Random Forests. [PDF]
Kimura S +4 more
europepmc +1 more source

