Results 81 to 90 of about 1,721,209 (309)

The Impact of Tilburg Frailty on Poststroke Fatigue in First‐Ever Stroke Patients: A Cross‐Sectional Study With Unified Measurement Tools and Improved Statistics

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Poststroke fatigue (PSF) and frailty share substantial overlap in their manifestations, yet previous research has yielded conflicting results due to the use of heterogeneous frailty assessment tools. Objective To evaluate the independent impact of frailty on PSF using a unified measurement system (Tilburg Frailty Indicator, TFI ...
Chuan‐Bang Chen, Xiao‐Xue Wang, Shao‐Rui Bao, Sui‐Li Lin, Mei‐Chun Shu, Xi‐Xi Ye, Wen‐Jie Cong   +6 more
wiley   +1 more source

Bioacoustic Classification of Antillean Manatee Vocalization Spectrograms Using Deep Convolutional Neural Networks

Applied Sciences, 2020
We evaluated the potential of using convolutional neural networks in classifying spectrograms of Antillean manatee (Trichechus manatus manatus) vocalizations. Spectrograms using binary, linear and logarithmic amplitude formats were considered.
Fernando Merchan, Ariel Guerra, Héctor Poveda, Héctor M. Guzmán, Javier E. Sanchez-Galan   +4 more
doaj   +1 more source

Design and Development of a Deep Learning-Based Model for Anomaly Detection in IoT Networks

IEEE Access, 2021
The growing development of IoT (Internet of Things) devices creates a large attack surface for cybercriminals to conduct potentially more destructive cyberattacks; as a result, the security industry has seen an exponential increase in cyber-attacks. Many
Imtiaz Ullah, Qusay H. Mahmoud
doaj   +1 more source

Probabilistic Binary Neural Networks

, 2018
Low bit-width weights and activations are an effective way of combating the increasing need for both memory and compute power of Deep Neural Networks. In this work, we present a probabilistic training method for Neural Network with both binary weights and activations, called BLRNet.
Peters, Jorn W. T., Welling, Max
openaire   +2 more sources

Impact of APOE ε4 Genotype Load on Cognitive Function and Lipid Metabolism in Patients With Cerebral Small Vessel Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Apolipoprotein ε4 (APOE ε4) is a potent genetic risk factor for Alzheimer's disease (AD). However, its role in cerebral small vessel disease (CSVD) remains unclear. Given the clinical and pathological similarities between CSVD and AD, this study aimed to investigate the associations of APOE ε4 gene dosage with cognitive function and
Tingru Jin, Haocheng Yang, Feng Liu, Sihao Lin, Junru Hu, Jian Wang, Yulan Gou   +6 more
wiley   +1 more source

A combined method of formation of a cryptographic key with secret modification of the results of synchronization of artificial neural networks

Системный анализ и прикладная информатика, 2021
This article discusses one of the ways to generate a common cryptographic key using synchronized artificial neural networks. This option is based on a combined method of forming a cryptographic key [1].
M. L. Radziukevich
doaj   +1 more source

Network Localization of Fatigue in Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Fatigue is among the most common symptoms and one of the main factors determining the quality of life in multiple sclerosis (MS). However, the neurobiological mechanisms underlying fatigue are not fully understood. Here we studied lesion locations and their connections in individuals with MS, aiming to identify brain networks ...
Olli Likitalo, Jaakko Kungshamn, Albert Bellmunt‐Gil, Silvia Tommasin, Abhineet Ojha, Matias Viitala, Juho Aaltonen, Jyrki Lötjönen, Juha Koikkalainen, Pauli Ylikotila, Patrizia Pantano, Merja Soilu‐Hänninen, Juho Joutsa   +12 more
wiley   +1 more source

ReBNet: Residual Binarized Neural Network

, 2018
This paper proposes ReBNet, an end-to-end framework for training reconfigurable binary neural networks on software and developing efficient accelerators for execution on FPGA.
Ghasemzadeh, Mohammad, Koushanfar, Farinaz, Samragh, Mohammad   +2 more
core   +1 more source

Fibrinogen Changes Before and After Intravenous Thrombolysis as Predictors of Cerebral Injury and Clinical Outcomes in Acute Ischemic Stroke: A Multicenter Prospective Cohort Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Plasma fibrinogen is essential in thrombosis and fibrinolysis, yet its dynamic changes pre‐ and post‐intravenous thrombolysis (IVT) for predicting brain injury severity and prognosis in acute ischemic stroke (AIS) patients remain unclear.
Wenhai Zhai, Yang Qu, Reziya Abuduxukuer, Kejia Zhang, Peng Zhang, Xin Tang, Huaimei Zhang, Lijuan Wang, Lichong Yang, Shuangxu Tan, Zhimei Yuan, Ce Han, Lili He, Yuping Zheng, Fenglan Zhao, Lijie Guo, Ligang Jiang, Jinfeng Li, Yongfei Jiang, Xuexia Zou, Dan Xu, Han Xu, Xiaojia Wang, Yingbin Qi, Xuefeng Hu, Yu Zhang, Zhen‐Ni Guo, Hang Jin, on behalf of the Biomarkers of Brain Injury Investigator Study Group   +28 more
wiley   +1 more source

On the Universal Approximation Property and Equivalence of Stochastic Computing-based Neural Networks and Binary Neural Networks

, 2018
Large-scale deep neural networks are both memory intensive and computation-intensive, thereby posing stringent requirements on the computing platforms. Hardware accelerations of deep neural networks have been extensively investigated in both industry and
Li, Jiayu, Lin, Xue, Tang, Jian, Wang, Siyue, Wang, Yanzhi, Wen, Wujie, Yuan, Bo, Zhan, Zheng, Zhao, Liang   +8 more
core   +1 more source