AIMC Topic: Attention

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Deep pyramid local attention neural network for cardiac structure segmentation in two-dimensional echocardiography.

Medical image analysis Oct 18, 2020
Automatic semantic segmentation in 2D echocardiography is vital in clinical practice for assessing various cardiac functions and improving the diagnosis of cardiac diseases. However, two distinct problems have persisted in automatic segmentation in 2...
Humans Ultrasonography Heart Attention Neural Networks, Computer Echocardiography
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Detecting and Responding to Information Overload With an Adaptive User Interface.

Human factors Oct 15, 2020
OBJECTIVE: The objective of this study was to develop and evaluate an adaptive user interface that could detect states of operator information overload and calibrate the amount of information on the screen.
Humans Workload Attention Task Performance and Analysis Machine Learning User-Computer Interface
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Effective attention-based network for syndrome differentiation of AIDS.

BMC medical informatics and decision making Oct 15, 2020
BACKGROUND: Syndrome differentiation aims at dividing patients into several types according to their clinical symptoms and signs, which is essential for traditional Chinese medicine (TCM). Several previous works were devoted to employing the classica...
Medicine, Chinese Traditional Attention Diagnosis, Computer-Assisted Acquired Immunodeficiency Syndrome Neural Networks, Computer Algorithms Humans
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Reverse graph self-attention for target-directed atomic importance estimation.

Neural networks : the official journal of the International Neural Network Society Oct 8, 2020
Estimating the importance of each atom in a molecule is one of the most appealing and challenging problems in chemistry, physics, and materials science. The most common way to estimate the atomic importance is to compute the electronic structure usin...
Molecular Conformation Nuclear Energy Machine Learning Electronics Humans Attention Neural Networks, Computer
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Image manipulation with natural language using Two-sided Attentive Conditional Generative Adversarial Network.

Neural networks : the official journal of the International Neural Network Society Sep 12, 2020
Altering the content of an image with photo editing tools is a tedious task for an inexperienced user, especially, when modifying the visual attributes of a specific object in an image without affecting other constituents such as background etc. To s...
Natural Language Processing Attention Humans Neural Networks, Computer Image Processing, Computer-Assisted
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Deep learning with attention supervision for automated motion artefact detection in quality control of cardiac T1-mapping.

Artificial intelligence in medicine Sep 7, 2020
Cardiac magnetic resonance quantitative T1-mapping is increasingly used for advanced myocardial tissue characterisation. However, cardiac or respiratory motion can significantly affect the diagnostic utility of T1-maps, and thus motion artefact detec...
Magnetic Resonance Imaging Attention Quality Control Algorithms Deep Learning Image Interpretation, Computer-Assisted Artifacts Humans
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fMRI volume classification using a 3D convolutional neural network robust to shifted and scaled neuronal activations.

NeuroImage Sep 5, 2020
Deep-learning methods based on deep neural networks (DNNs) have recently been successfully utilized in the analysis of neuroimaging data. A convolutional neural network (CNN) is a type of DNN that employs a convolution kernel that covers a local area...
Young Adult Adult Support Vector Machine Magnetic Resonance Imaging Male Humans Auditory Perception Neural Networks, Computer Brain Psychomotor Performance Brain Mapping Motor Activity Attention Visual Perception
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Multi-dimensional predictions of psychotic symptoms via machine learning.

Human brain mapping Sep 1, 2020
The diagnostic criteria for schizophrenia comprise a diverse range of heterogeneous symptoms. As a result, individuals each present a distinct set of symptoms despite having the same overall diagnosis. Whilst previous machine learning studies have pr...
Hallucinations Auditory Perception Humans Motivation Prognosis Anhedonia Female Machine Learning Adolescent Male Schizophrenia Psychotic Disorders Young Adult Magnetic Resonance Imaging Middle Aged Attention Adult Functional Neuroimaging
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MGAT: Multi-view Graph Attention Networks.

Neural networks : the official journal of the International Neural Network Society Aug 27, 2020
Multi-view graph embedding is aimed at learning low-dimensional representations of nodes that capture various relationships in a multi-view network, where each view represents a type of relationship among nodes. Multitudes of existing graph embedding...
Neural Networks, Computer Machine Learning Attention Algorithms
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Pain intensity estimation based on a spatial transformation and attention CNN.

PloS one Aug 21, 2020
Models designed to detect abnormalities that reflect disease from facial structures are an emerging area of research for automated facial analysis, which has important potential value in smart healthcare applications. However, most of the proposed mo...
Image Processing, Computer-Assisted Humans Attention Neural Networks, Computer Pain Perception
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