Results 111 to 120 of about 914,662 (294)
Impact of Asymptomatic Intracranial Hemorrhage on Outcome After Endovascular Stroke Treatment
ABSTRACT Background Endovascular treatment (EVT) achieves high rates of recanalization in acute large‐vessel occlusion (LVO) stroke, but functional recovery remains heterogeneous. While symptomatic intracranial hemorrhage (sICH) has been well studied, the prognostic impact of asymptomatic intracranial hemorrhage (aICH) after EVT is less certain ...
Shihai Yang +22 more
wiley +1 more source
ABSTRACT Background Accessing brain magnetic resonance imaging (MRI) can be challenging, especially for underserved patients, which may lead to disparities in neurological diagnosis. Method This mixed‐methods study enrolled adults with one of four neurological disorders: mild cognitive impairment or dementia of the Alzheimer type, multiple sclerosis ...
Maya L. Mastick +19 more
wiley +1 more source
Multi-Faceted Adaptive Token Pruning for Efficient Remote Sensing Image Segmentation
Global context information is essential for semantic segmentation of remote sensing (RS) images. Due to their remarkable capability to capture global context information and model long-range dependencies, vision transformers have demonstrated great ...
Chuge Zhang, Jian Yao
doaj +1 more source
HMC: Hybrid model compression method based on layer sensitivity grouping. [PDF]
Yang G, Yu S, Yang H, Nie Z, Wang J.
europepmc +1 more source
Developmental and Epileptic Encephalopathy due to Biallelic Pathogenic Variants in PIGM
ABSTRACT Objective PIGM encodes a critical enzyme in the glycosylphosphatidylinositol (GPI)‐anchor biosynthesis pathway. While promoter‐region mutations in PIGM have been associated with a relatively mild phenotype characterized by portal vein thrombosis and absence seizures, recent evidence suggests that coding‐region mutations result in a more severe
Júlia Sala‐Coromina +11 more
wiley +1 more source
Convolutional Neural Network Compression via Dynamic Parameter Rank Pruning
While Convolutional Neural Networks (CNNs) excel at learning complex latent-space representations, their over-parameterization can lead to overfitting and reduced performance, particularly with limited data.
Manish Sharma +3 more
doaj +1 more source
LAD: Layer-Wise Adaptive Distillation for BERT Model Compression. [PDF]
Lin YJ, Chen KY, Kao HY.
europepmc +1 more source
Ketogenic Diet as an Epigenetic Therapy in SETD1B‐Related Epilepsy
ABSTRACT Histone lysine methyltransferases such as SETD1B regulate chromatin structure and gene transcription. Ketone bodies, including butyrate, act as histone deacetylase inhibitors. We report a 4‐year‐old boy with SETD1B‐related absence epilepsy, refractory to conventional medications, who achieved sustained > 90% seizure reduction on the Modified ...
Erica Tsang +10 more
wiley +1 more source
Global Structural Knowledge Distillation for Semantic Segmentation
Knowledge distillation (KD) has become a cornerstone for compressing deep neural networks, allowing a smaller student model to learn from a larger teacher model.
Hyejin Park +3 more
doaj +1 more source
Mitigating carbon footprint for knowledge distillation based deep learning model compression. [PDF]
Rafat K +7 more
europepmc +1 more source

