Results 91 to 100 of about 11,210,090 (249)

White Matter Microstructural Abnormalities in Neonatal Onset Genetic Epilepsy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Recent evidence indicates that epilepsy is associated with abnormal white matter. If seizures alter white matter, then the impact upon network function, epileptogenesis, and cognition could be pronounced in neonates undergoing rapid developmental myelination. Neonates with epilepsy due to nonstructural genetic causes provide a unique
Amanda G. Sandoval Karamian, Tianjia Zhu, Hao Huang, Shavonne L. Massey, Mark P. Fitzgerald, Darshana Parikh, Arastoo Vossough, Ingo Helbig, Nicholas S. Abend   +8 more
wiley   +1 more source

Single image denoising based on adaptive fusion dual‐domain network

IET Image Processing
Deep learning‐based‐image denoising methods have recently achieved excellent performance by learning non‐linear mapping in the spatial domain. However, these methods fail to address the noise without specific distribution because they only use features ...
Zhiwei Jiang, Zhizhong Xue, Jue Wang, Yibiao Hu, Qiufu Zheng   +4 more
doaj   +1 more source

Cognitive and Neuroimaging Divergence Between Juvenile and Adult FUS Amyotrophic Lateral Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder characterized by progressive motor neuron degeneration. Fused in sarcoma (FUS)‐associated juvenile ALS (jALS) represents a distinct and aggressive subgroup with rapid deterioration and poor prognosis.
Alexandra V. Jürs, Marcel Naumann, Annaliis Lehto, Hanna Schön, Jens Kurth, Johannes Prudlo, Andreas Hermann, Elisabeth Kasper   +7 more
wiley   +1 more source

Digital Cognitive Phenotyping for Differential Diagnosis and Monitoring in Neurological Conditions

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To assess the utility, accessibility, and equivalence to supervised scales of online cognitive assessment in older individuals with cognitive impairment. Methods Patients with Alzheimer's disease (AD, n = 31), idiopathic normal pressure hydrocephalus (iNPH, n = 26), and traumatic brain injury (TBI, n = 23) completed online cognitive ...
Martina Del Giovane, Valentina Giunchiglia, Michael C. B. David, Magdalena A. Kolanko, William R. Trender, Peter J. Hellyer, Harmeena Kaur, David J. Sharp, Christopher Carswell, Paresh A. Malhotra, Adam Hampshire   +10 more
wiley   +1 more source

Digital Cognitive Testing in Mitochondrial Disease: Validity and Challenges for Clinical Trial Use

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Primary mitochondrial disease is a group of genetic disorders caused by pathogenic variants in nuclear or mitochondrial DNA, often resulting in progressive neurodegeneration and cognitive decline. Current management is primarily supportive, though recent research offers hope for disease‐modifying treatments in the future.
Oksana Pogoryelova, Jan Smeitink, Herma Renkema, Rosabeth White, Frankie Barton, Rachel Lyon, Jane Newman, Aye Moe, Yi Shiau Ng, Grainne Siobhan Gorman   +9 more
wiley   +1 more source

Frequency domain error analysis in ultra-precision flycutting

, 2014
In some special fields such as precision optics, the part surface has strict requirements on the frequency domain errors, besides the conventional spatial domain errors such as surface roughness error.
Chen GD(陈国达), Chen JX(陈家轩), Sun YZ(孙雅洲), Wang, Heran, Liang YC(梁迎春)   +4 more
core  

MTFSC: A Self-Supervised Transferable Representation Learning Algorithm for Diagnosing Cross-Machine Faults in Rotating Machinery

Algorithms
Rotating machinery is a key component in modern industry, and its operating condition directly affects equipment safety and production reliability. However, discrepancies among different machines cause source–target distribution shifts, while fault ...
Yuan Xu, Enyong Xu, Yingnan Gao, Zhenzhen Jin   +3 more
doaj   +1 more source

Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif, Diane Demailly, Gabriella A. Horvàth, Juan Dario Ortigoza Escobar, Nathalie Dorison, Mayté Castro Jiménez, Cécile A. Hubsch, Thomas Wirth, Gun‐Marie Hariz, Sophie Huby, Morgan Dornadic, Zohra Souei, Muhammad Mushhood Ur Rehman, Simone Hemm, Mehdi Boulaymen, Eduardo M. Moraud, Jocelyne Bloch, Xavier Vasques   +17 more
wiley   +1 more source

Research on Frequency-Domain Learning-Based Fault Diagnosis Methods in Nuclear Power Plants via a Lightweight Complex-Valued Neural Network

Energies
Nuclear power plant (NPP) fault diagnosis is critical to ensure the safe, stable and economic operation of nuclear facilities. Existing deep learning-based NPP fault diagnosis methods primarily extract features from the temporal and spatial domain. Given
Zijian Wu, Zhe Dong, Xiaojin Huang
doaj   +1 more source

Temporal Interference Stimulation of Centromedian‐Parafascicular Complex in Disorders of Consciousness: A Pilot Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Treatment of disorders of consciousness (DoC) remains a major clinical challenge, and noninvasive, targeted modulation of deep brain structures has emerged as a promising therapeutic strategy. We aimed to evaluate the feasibility/safety and preliminary effects of thalamic temporal interference stimulation (TIS) targeting centromedian‐
Gengyao Hu, Changgeng Song, Dianwei Wu, Xiaoqian Niu, Jianmin Hao, Lijuan Liu, Xiaogang Kang, Wen Jiang   +7 more
wiley   +1 more source