Results 101 to 110 of about 2,445,824 (337)
Learning text representation using recurrent convolutional neural network with highway layers [PDF]
Recently, the rapid development of word embedding and neural networks has brought new inspiration to various NLP and IR tasks. In this paper, we describe a staged hybrid model combining Recurrent Convolutional Neural Networks (RCNN) with highway layers ...
Luo, Rui+3 more
core +1 more source
A PANoptosis‐Based Signature for Survival and Immune Predication in Glioblastoma Multiforme
ABSTRACT Objective PANoptosis is a concept of total cell death characterized by pyroptosis, apoptosis, and necroptosis. We aimed to explore the clinical significance of PANoptosis‐related genes (PARGs) in glioblastoma multiforme (GBM). Methods Expression profiles of GBM were downloaded from the XENA database as a training dataset to construct a ...
Jun Yang+4 more
wiley +1 more source
It has been known for discrete-time recurrent neural networks (NNs) that binary-state models using the Heaviside activation function (with Boolean outputs 0 or 1) are equivalent to finite automata (level 3 in the Chomsky hierarchy), while analog-state NNs with rational weights, employing the saturated-linear function (with real-number outputs in the ...
openaire +4 more sources
ABSTRACT Objective Amygdala enlargement has been the subject of controversial studies regarding its significance in terms of pathogenicity both in epilepsy and in psychiatric comorbidities such as anxiety, depression, and post‐traumatic stress disorder.
Hélène Mourre+15 more
wiley +1 more source
ABSTRACT Dopaminergic medication and deep brain stimulation (DBS) improve motor symptoms in Parkinson's disease (PD), but levodopa response alone may not predict DBS outcomes. We retrospectively analyzed 19 PD patients undergoing levodopa challenges with and without prior transcranial direct current stimulation targeting a defined PD response network ...
Lukas L. Goede+3 more
wiley +1 more source
We present N2Net, a system that implements binary neural networks using commodity switching chips deployed in network switches and routers. Our system shows that these devices can run simple neural network models, whose input is encoded in the network packets' header, at packet processing speeds (billions of packets per second).
Siracusano, Giuseppe, Bifulco, Roberto
openaire +2 more sources
Translating Muscle RNAseq Into the Clinic for the Diagnosis of Muscle Diseases
ABSTRACT Objective Approximately half of patients with hereditary myopathies remain without a definitive genetic diagnosis after DNA next‐generation sequencing (NGS). Here, we implemented transcriptome analysis of muscle biopsies as a complementary diagnostic tool for patients with muscle disease but no definitive genetic diagnosis after exome ...
Alba Segarra‐Casas+24 more
wiley +1 more source
An Improved Recurrent Neural Network for Industrial IoT Botnet Attack Detection
This research aims to improve the Industrial Internet of Things (IIoT) security, which fosters technological confidence and promotes expansion. The IIoT is mainly used in manufacturing, oil, and gas to avoid botnet attacks.
G. Suneetha, D.H. Priya
doaj +1 more source
Analysis of the Neural Network Regulating the Cardio-Renal System in the Central Nervous System ofHelix pomatiaL. [PDF]
Katalin S.-Rózsa
openalex +1 more source
Pathway Analyses of Inherited Neuropathies Identify Putative Common Mechanisms of Axon Degeneration
ABSTRACT Objective Inherited neuropathies (IN) are associated with over 100 different genetic mutations presenting with a variety of phenotypes. This complexity suggests multiple pathways may converge onto a limited number of downstream pathways to effect axonal injury.
Christopher R. Cashman+2 more
wiley +1 more source