AIMC Topic: Attention

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Driving Cognitive Alertness Detecting Using Evoked Multimodal Physiological Signals Based on Uncertain Self-Supervised Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Jun 13, 2024
Multimodal physiological signals play a pivotal role in drivers' perception of work stress. However, the scarcity of labels and the multitude of modalities render the utilization of physiological signals for driving cognitive alertness detection chal...
Attention Cognition Humans Uncertainty Algorithms Heart Rate Electroencephalography Automobile Driving Supervised Machine Learning Male Linear Models Entropy
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Classification of short and long term mild traumatic brain injury using computerized eye tracking.

Scientific reports Jun 3, 2024
Accurate, and objective diagnosis of brain injury remains challenging. This study evaluated useability and reliability of computerized eye-tracker assessments (CEAs) designed to assess oculomotor function, visual attention/processing, and selective a...
Machine Learning Female Reproducibility of Results Young Adult Humans Brain Concussion Post-Concussion Syndrome Saccades Eye-Tracking Technology Adult Eye Movements Reflex, Vestibulo-Ocular Male Attention Middle Aged
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Attention-Like Multimodality Fusion With Data Augmentation for Diagnosis of Mental Disorders Using MRI.

IEEE transactions on neural networks and learning systems Jun 3, 2024
The globally rising prevalence of mental disorders leads to shortfalls in timely diagnosis and therapy to reduce patients' suffering. Facing such an urgent public health problem, professional efforts based on symptom criteria are seriously overstretc...
Female Young Adult Adult Male Mental Disorders Autism Spectrum Disorder Brain Attention Image Interpretation, Computer-Assisted Neuroimaging Attention Deficit Disorder with Hyperactivity Magnetic Resonance Imaging Multimodal Imaging Schizophrenia Neural Networks, Computer Algorithms Humans
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Spiking generative adversarial network with attention scoring decoding.

Neural networks : the official journal of the International Neural Network Society Jun 1, 2024
Generative models based on neural networks present a substantial challenge within deep learning. As it stands, such models are primarily limited to the domain of artificial neural networks. Spiking neural networks, as the third generation of neural n...
Neurons Attention Algorithms Brain Animals Models, Neurological Action Potentials Deep Learning Mice Humans Neural Networks, Computer
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A syntactic evidence network model for fact verification.

Neural networks : the official journal of the International Neural Network Society Jun 1, 2024
In natural language processing, fact verification is a very challenging task, which requires retrieving multiple evidence sentences from a reliable corpus to verify the authenticity of a claim. Although most of the current deep learning methods use t...
Neural Networks, Computer Language Deep Learning Natural Language Processing Humans Attention Semantics
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Graph convolutional network with attention mechanism improve major depressive depression diagnosis based on plasma biomarkers and neuroimaging data.

Journal of affective disorders May 31, 2024
BACKGROUND: The absence of clinically-validated biomarkers or objective protocols hinders effective major depressive disorder (MDD) diagnosis. Compared to healthy control (HC), MDD exhibits anomalies in plasma protein levels and neuroimaging presenta...
Attention Neuroimaging Gray Matter Orexins Depressive Disorder, Major Case-Control Studies Magnetic Resonance Imaging Adult Male Middle Aged Humans Biomarkers Neural Networks, Computer Algorithms Female Machine Learning Cytokines
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Seizure Detection Based on Lightweight Inverted Residual Attention Network.

International journal of neural systems May 31, 2024
Timely and accurately seizure detection is of great importance for the diagnosis and treatment of epilepsy patients. Existing seizure detection models are often complex and time-consuming, highlighting the urgent need for lightweight seizure detectio...
Neural Networks, Computer Electroencephalography Humans Seizures Signal Processing, Computer-Assisted Attention
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Multiscale knowledge distillation with attention based fusion for robust human activity recognition.

Scientific reports May 30, 2024
Knowledge distillation is an effective approach for training robust multi-modal machine learning models when synchronous multimodal data are unavailable. However, traditional knowledge distillation techniques have limitations in comprehensively trans...
Attention Human Activities Humans Machine Learning Neural Networks, Computer Algorithms
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EEG Emotion Recognition Network Based on Attention and Spatiotemporal Convolution.

Sensors (Basel, Switzerland) May 27, 2024
Human emotions are complex psychological and physiological responses to external stimuli. Correctly identifying and providing feedback on emotions is an important goal in human-computer interaction research. Compared to facial expressions, speech, or...
Emotions Electroencephalography Signal Processing, Computer-Assisted Attention Neural Networks, Computer Humans Algorithms Brain
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An automated approach for predicting HAMD-17 scores via divergent selective focused multi-heads self-attention network.

Brain research bulletin May 26, 2024
This study introduces the Divergent Selective Focused Multi-heads Self-Attention Network (DSFMANet), an innovative deep learning model devised to automatically predict Hamilton Depression Rating Scale-17 (HAMD-17) scores in patients with depression. ...
Attention Psychiatric Status Rating Scales Depression Electroencephalography Humans Male Deep Learning Female Adult
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