AIMC Topic: Attention

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Linear versus deep learning methods for noisy speech separation for EEG-informed attention decoding.

Journal of neural engineering Aug 19, 2020
OBJECTIVE: A hearing aid's noise reduction algorithm cannot infer to which speaker the user intends to listen to. Auditory attention decoding (AAD) algorithms allow to infer this information from neural signals, which leads to the concept of neuro-st...
Electroencephalography Attention Acoustic Stimulation Speech Perception Deep Learning Speech
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High tissue contrast image synthesis via multistage attention-GAN: Application to segmenting brain MR scans.

Neural networks : the official journal of the International Neural Network Society Aug 18, 2020
Magnetic resonance imaging (MRI) presents a detailed image of the internal organs via a magnetic field. Given MRI's non-invasive advantage in repeated imaging, the low-contrast MR images in the target area make segmentation of tissue a challenging pr...
Infant Magnetic Resonance Imaging Attention Neural Networks, Computer Brain Humans Image Enhancement Brain Neoplasms
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Attention-Enriched Deep Learning Model for Breast Tumor Segmentation in Ultrasound Images.

Ultrasound in medicine & biology Jul 21, 2020
Incorporating human domain knowledge for breast tumor diagnosis is challenging because shape, boundary, curvature, intensity or other common medical priors vary significantly across patients and cannot be employed. This work proposes a new approach t...
Humans Deep Learning Attention Female Models, Theoretical Image Enhancement Breast Neoplasms Ultrasonography, Mammary
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Automated diagnosis of bone metastasis based on multi-view bone scans using attention-augmented deep neural networks.

Medical image analysis Jul 18, 2020
Bone scintigraphy is accepted as an effective diagnostic tool for whole-body examination of bone metastasis. However, the manual analysis of bone scintigraphy images requires extensive experience and is exhausting and time-consuming. An automated dia...
Humans Neural Networks, Computer Reproducibility of Results Attention
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Decoding attention control and selection in visual spatial attention.

Human brain mapping Jun 16, 2020
Event-related potentials (ERPs) are used extensively to investigate the neural mechanisms of attention control and selection. The univariate ERP approach, however, has left important questions inadequately answered. We addressed two questions by appl...
Visual Perception Space Perception Executive Function Brain Waves Functional Laterality Evoked Potentials Male Adolescent Psychomotor Performance Support Vector Machine Female Electroencephalography Cues Young Adult Humans Attention Adult
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Can robotic gait rehabilitation plus Virtual Reality affect cognitive and behavioural outcomes in patients with chronic stroke? A randomized controlled trial involving three different protocols.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Jun 13, 2020
BACKGROUND: The rehabilitation of cognitive and behavioral abnormalities in individuals with stroke is essential for promoting patient's recovery and autonomy. The aim of our study is to evaluate the effects of robotic neurorehabilitation using Lokom...
Gait Exercise Therapy Attention Activities of Daily Living Affect Virtual Reality Exposure Therapy Adult Disability Evaluation Mental Health Italy Male Stroke Cognition Humans Recovery of Function Treatment Outcome Female Chronic Disease Health Status Stroke Rehabilitation Middle Aged Robotics Executive Function Quality of Life Time Factors
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Auditory attention tracking states in a cocktail party environment can be decoded by deep convolutional neural networks.

Journal of neural engineering Jun 12, 2020
OBJECTIVE: A deep convolutional neural network (CNN) is a method for deep learning (DL). It has a powerful ability to automatically extract features and is widely used in classification tasks with scalp electroencephalogram (EEG) signals. However, th...
Humans Signal-To-Noise Ratio Entropy Neural Networks, Computer Electroencephalography Attention
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Single-Trial EEG Responses Classified Using Latency Features.

International journal of neural systems Jun 2, 2020
Covert attention has been repeatedly shown to impact on EEG responses after single and repeated practice sessions. Machine learning techniques are increasingly adopted to classify single-trial EEG responses thereby primarily relying on amplitude-base...
Cerebral Cortex Practice, Psychological Signal Processing, Computer-Assisted Attention Psychomotor Performance Humans Machine Learning Aged Longitudinal Studies Neuronal Plasticity Electroencephalography
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Bio-semantic relation extraction with attention-based external knowledge reinforcement.

BMC bioinformatics May 24, 2020
BACKGROUND: Semantic resources such as knowledge bases contains high-quality-structured knowledge and therefore require significant effort from domain experts. Using the resources to reinforce the information retrieval from the unstructured text may ...
Attention Humans Semantics Databases, Genetic Neural Networks, Computer Publications Algorithms Knowledge Bases
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Extracting drug-drug interactions from texts with BioBERT and multiple entity-aware attentions.

Journal of biomedical informatics May 23, 2020
Drug-drug interactions (DDIs) extraction is one of the important tasks in the field of biomedical relation extraction, which plays an important role in the field of pharmacovigilance. Previous neural network based models have achieved good performanc...
Semantics Neural Networks, Computer Pharmaceutical Preparations Drug Interactions Attention
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