Results 61 to 70 of about 92,534 (217)

Combination of Recursive and Recurrent Neural Networks for Aspect-Based Sentiment Analysis Using Inter-Aspect Relations

IEEE Access, 2020
Sentiment analysis studies in the literature mostly use either recurrent or recursive neural network models. Recurrent models capture the effect of time and propagate the information of sentiment labels in a review throughout the word sequence. Recursive
Cem Rifki Aydin, Tunga Gungor
doaj   +1 more source

Super‐Refractory Status Epilepticus (SRSE) in a Patient With Compound Heterozygous OPA1 Variants: Case Report and Literature Review

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Super‐Refractory Status Epilepticus (SRSE) is a rare, life‐threatening neurological emergency with unclear etiology in many cases. Mitochondrial dysfunction, often due to disease‐causing genetic variants, is increasingly recognized as a cause, with each gene producing distinct pathophysiological mechanisms.
Pouria Mohammadi, Lara Basovic, Christopher Michael McGraw   +2 more
wiley   +1 more source

Experimental Study on Long Short-term Memory Networks for Identifying P-wave Primary Phase

CT Lilun yu yingyong yanjiu
Identifying primary phases of seismic waveforms is a routine task in seismic data processing. Owing to the low efficiency of manual identification and the influence of human subjective factors, many methods for the automatic identification of the primary
Tianzhe WANG, Wanji ZHANG, Shanbo QI, Guoming JIANG   +3 more
doaj   +1 more source

Structure–Function Decoupling of the Sensorimotor and Default Mode Networks in Black Americans With MS

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background and Objectives Multiple sclerosis (MS) exhibits racially disparate rates of disease progression. Black people with MS (B‐PwMS) experience a more severe disease course than non‐Hispanic White people with MS (NHW‐PwMS). Here we investigated structural and functional connectivity as well as structure–function decoupling in the ...
Emilio Cipriano, Giacomo Boffa, Maria Petracca, Marta Ponzano, Nicole Graziano, Claire Wigley, Claire Riley, Jonathan Howard, Pietro Bontempi, Sylvia Klineova, Fred Lublin, Matilde Inglese   +11 more
wiley   +1 more source

NLOS Identification in WLANs Using Deep LSTM with CNN Features

Sensors, 2018
Identifying channel states as line-of-sight or non-line-of-sight helps to optimize location-based services in wireless communications. The received signal strength identification and channel state information are used to estimate channel conditions for ...
Viet-Hung Nguyen, Minh-Tuan Nguyen, Jeongsik Choi, Yong-Hwa Kim   +3 more
doaj   +1 more source

Vestibular Patient Journey: Insights From Vestibular Disorders Association (VeDA) Registry

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Vestibular symptoms impose a high burden of disability. Understanding real‐world diagnostic and treatment pathways can identify care gaps and guide interventions. We aimed to characterize symptom profiles, diagnostic trends, provider involvement, and treatment patterns in vestibular disorders.
Ali Rafati, Sami I. Nassar, Shaun A. Nguyen, Patricia L. Gerend, Michael C. Schubert, Michael T. Teixido, Frederick A. Godley, Joel A. Goebel, Cynthia A. Ryan, Habib G. Rizk, Amir Kheradmand   +10 more
wiley   +1 more source

Baseline Regional Cholinergic Denervation Predicts Cognitive Trajectories in Moderate Parkinson Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Cognitive decline is a disabling and variable feature of Parkinson disease (PD). While cholinergic system degeneration is linked to cognitive impairments in PD, most prior research reported cross‐sectional associations. We aimed to fill this gap by investigating whether baseline regional cerebral vesicular acetylcholine transporter ...
Taylor Brown, Giulia Carli, Prabesh Kanel, Stiven Roytman, Jaimie Barr, Nicolaas I. Bohnen, Roger L. Albin   +6 more
wiley   +1 more source

Long short-term memory neural networks for forecasting sea level and seiche occurrences in the Maltese Islands

Array
The ability to predict seiches can help prevent the damage and mitigate the risks associated with these natural phenomena. This paper presents a novel approach for seiche prediction in Marsaxlokk, Malta, using Long Short-Term Memory (LSTM) neural network
Nicole Borg, Fiona Sammut, David Suda, Adam Gauci, Alan Deidun   +4 more
doaj   +1 more source

Multiclass classification of myocardial infarction with convolutional and recurrent neural networks for portable ECG devices

Informatics in Medicine Unlocked, 2018
Myocardial infarction (MI) is a medical emergency for which the early detection of symptoms is desirable. The prevalence of portable electrocardiogram (ECG) devices makes frequent screening for MI possible. In this study, we develop an MI classifier that
Hin Wai Lui, King Lau Chow
doaj   +1 more source

Efficacy of Intermittent Theta‐Burst Stimulation for Prolonged Disorders of Consciousness: A Prospective, Randomized, Controlled Trial

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Emerging evidence suggests that low‐frequency neural oscillations are dynamically regulated by consciousness levels, with the recovery of low cortical activity potentially serving as a neurophysiological substrate for conscious emergence. Targeted enhancement of these low‐frequency rhythms in patients with disorders of consciousness
Chuan Xu, Jun Hu, Qianqian Wu, Min Wu, Yamei Yu, Hangcheng Li, Jian Gao, Jingqi Li, Nai Ding, Jie Yu, Benyan Luo   +10 more
wiley   +1 more source