AIMC Topic: Brain
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Knowledge Distillation Guided Interpretable Brain Subgraph Neural Networks for Brain Disorder Exploration.
IEEE transactions on neural networks and learning systems
Feb 6, 2025
The human brain is a highly complex neurological system that has been the subject of continuous exploration by scientists. With the help of modern neuroimaging techniques, there has been significant progress made in brain disorder analysis. There is ...
Community Graph Convolution Neural Network for Alzheimer's Disease Classification and Pathogenetic Factors Identification.
IEEE transactions on neural networks and learning systems
Feb 6, 2025
As a complex neural network system, the brain regions and genes collaborate to effectively store and transmit information. We abstract the collaboration correlations as the brain region gene community network (BG-CN) and present a new deep learning a...
Neural mechanisms, influencing factors and interventions in empathic pain.
Neuropharmacology
Feb 4, 2025
Empathic pain, defined as the emotional resonance with the suffering of others, is akin to the observer's own experience of pain and is vital for building and sustaining positive interpersonal relationships. Despite its importance, the neural mechani...
CQformer: Learning Dynamics Across Slices in Medical Image Segmentation.
IEEE transactions on medical imaging
Feb 4, 2025
Prevalent studies on deep learning-based 3D medical image segmentation capture the continuous variation across 2D slices mainly via convolution, Transformer, inter-slice interaction, and time series models. In this work, via modeling this variation b...
UTSRMorph: A Unified Transformer and Superresolution Network for Unsupervised Medical Image Registration.
IEEE transactions on medical imaging
Feb 4, 2025
Complicated image registration is a key issue in medical image analysis, and deep learning-based methods have achieved better results than traditional methods. The methods include ConvNet-based and Transformer-based methods. Although ConvNets can eff...
An Explainable Unified Framework of Spatio-Temporal Coupling Learning With Application to Dynamic Brain Functional Connectivity Analysis.
IEEE transactions on medical imaging
Feb 4, 2025
Time-series data such as fMRI and MEG carry a wealth of inherent spatio-temporal coupling relationship, and their modeling via deep learning is essential for uncovering biological mechanisms. However, current machine learning models for mining spatio...
M₂DC: A Meta-Learning Framework for Generalizable Diagnostic Classification of Major Depressive Disorder.
IEEE transactions on medical imaging
Feb 4, 2025
Psychiatric diseases are bringing heavy burdens for both individual health and social stability. The accurate and timely diagnosis of the diseases is essential for effective treatment and intervention. Thanks to the rapid development of brain imaging...
Prototype-Guided Graph Reasoning Network for Few-Shot Medical Image Segmentation.
IEEE transactions on medical imaging
Feb 4, 2025
Few-shot semantic segmentation (FSS) is of tremendous potential for data-scarce scenarios, particularly in medical segmentation tasks with merely a few labeled data. Most of the existing FSS methods typically distinguish query objects with the guidan...
EEG-based fatigue state evaluation by combining complex network and frequency-spatial features.
Journal of neuroscience methods
Feb 3, 2025
BACKGROUND: The proportion of traffic accidents caused by fatigue driving is increasing year by year, which has aroused wide concerns for researchers. In order to rapidly and accurately detect drivers' fatigue, this paper proposed an electroencephalo...
AFMDD: Analyzing Functional Connectivity Feature of Major Depressive Disorder by Graph Neural Network-Based Model.
Journal of computational biology : a journal of computational molecular cell biology
Feb 3, 2025
The extraction of biomarkers from functional connectivity (FC) in the brain is of great significance for the diagnosis of mental disorders. In recent years, with the development of deep learning, several methods have been proposed to assist in the di...
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