Results 281 to 290 of about 497,808 (317)

Unraveling Parkinson's disease motor subtypes: A deep learning approach based on spatiotemporal dynamics of EEG microstates

Lin Meng, Deyu Wang, Jun Ma, Yu Shi, Hong-Bo Zhao, Yanlin Wang, Qingqing Shi, Xiaodong Zhu, Dong Ming   +8 more
openalex   +1 more source

Action recognition in rehabilitation: combining 3D convolution and LSTM with spatiotemporal attention. [PDF]

Front Physiol
Yang F, Li S, Sun C, Li X, Xiao Z.
europepmc   +1 more source

Molecular Tools to Study and Control Dopaminergic Neurotransmission With Light

Medicinal Research Reviews, EarlyView.
ABSTRACT Dopaminergic neurotransmission is involved in several important brain functions, such as motor control, learning, reward‐motivated behavior, and emotions. Dysfunctions of dopaminergic system may lead to the development of various neurological and psychiatric disorders, like Parkinson's disease, schizophrenia, depression, and addictions ...
Galyna Maleeva, Carlo Matera, Silvia Roda, Alessio Colleoni, Marco De Amici, Pau Gorostiza   +5 more
wiley   +1 more source

Spatiotemporal Soil Moisture Prediction Using a Causal-Guided Deep Learning Model

Tonghai Wu, Lei Xu, Ziwei Pan, Ruinan Cai, Jin Dai, Shuang Yang, Xihao Zhang, Xi Zhang, Nengcheng Chen   +8 more
openalex   +1 more source

Multi scale convolutional neural network combining BiLSTM and attention mechanism for bearing fault diagnosis under multiple working conditions. [PDF]

Sci Rep
Dengfeng Z, Chaoyang T, Zhijun F, Yudong Z, Junjian H, Wenbin H.   +5 more
europepmc   +1 more source

Deep learning framework for interpretable quality control of echocardiography video

Medical Physics, EarlyView.
Abstract Background Echocardiography (echo) has become an indispensable tool in modern cardiology, offering real‐time imaging that helps clinicians evaluate heart function and identify abnormalities. Despite these advantages, the acquisition of high‐quality echo is time‐consuming, labor‐intensive, and highly subjective.
Liwei Du, Wufeng Xue, Zhanru Qi, Zhongqing Shi, Guanjun Guo, Xin Yang, Dong Ni, Jing Yao   +7 more
wiley   +1 more source

Leveraging multi-source data and teleconnection indices for enhanced runoff prediction using coupled deep learning models. [PDF]

Sci Rep
Li J, Ai P, Xiong C, Song Y.
europepmc   +1 more source

Robust deep learning model with attention framework for spatiotemporal forecasting of solar and wind energy production

Md. Shadman Abid, Razzaqul Ahshan, Mohammed Al‐Abri, Rashid Al-Abri   +3 more
openalex   +1 more source

Repeatability‐encouraging self‐supervised learning reconstruction for quantitative MRI

Magnetic Resonance in Medicine, EarlyView.
Abstract Purpose The clinical value of quantitative MRI hinges on its measurement repeatability. Deep learning methods to reconstruct undersampled quantitative MRI can accelerate reconstruction but do not aim to promote quantitative repeatability. This study proposes a repeatability‐encouraging self‐supervised learning (SSL) reconstruction method for ...
Zihao Chen, Zheyuan Hu, Yibin Xie, Debiao Li, Anthony G. Christodoulou   +4 more
wiley   +1 more source

High-throughput, unbiased single-molecule displacement mapping with deep learning reveals spatiotemporal heterogeneities in intracellular diffusivity

Junfeng Xia, Yi He, Zhipeng Zhang, Jinhong Yan, Ruirong Wang, Ming Tang, J. Chen, Jun Fan, Kun Chen   +8 more
openalex   +1 more source