AIMC Topic: Brain
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Tensor dictionary-based heterogeneous transfer learning to study emotion-related gender differences in brain.
Neural networks : the official journal of the International Neural Network Society
Dec 3, 2024
In practice, collecting auxiliary labeled data with same feature space from multiple domains is difficult. Thus, we focus on the heterogeneous transfer learning to address the problem of insufficient sample sizes in neuroimaging. Viewing subjects, ti...
A Machine learning classification framework using fused fractal property feature vectors for Alzheimer's disease diagnosis.
Brain research
Dec 3, 2024
Alzheimer's disease (AD) profoundly affects brain tissue and network structures. Analyzing the topological properties of these networks helps to understand the progression of the disease. Most studies focus on single-scale brain networks, but few add...
Machine learning based metabolomic and genetic profiles for predicting multiple brain phenotypes.
Journal of translational medicine
Dec 3, 2024
BACKGROUND: It is unclear regarding the association between metabolomic state/genetic risk score(GRS) and brain volumes and how much of variance of brain volumes is attributable to metabolomic state or GRS.
Deep learning-based segmentation of acute ischemic stroke MRI lesions and recurrence prediction within 1 year after discharge: A multicenter study.
Neuroscience
Dec 2, 2024
OBJECTIVE: To explore the performance of deep learning-based segmentation of infarcted lesions in the brain magnetic resonance imaging (MRI) of patients with acute ischemic stroke (AIS) and the recurrence prediction value of radiomics within 1 year a...
Portable, low-field magnetic resonance imaging for evaluation of Alzheimer's disease.
Nature communications
Dec 2, 2024
Portable, low-field magnetic resonance imaging (LF-MRI) of the brain may facilitate point-of-care assessment of patients with Alzheimer's disease (AD) in settings where conventional MRI cannot. However, image quality is limited by a lower signal-to-n...
LCGNet: Local Sequential Feature Coupling Global Representation Learning for Functional Connectivity Network Analysis With fMRI.
IEEE transactions on medical imaging
Dec 2, 2024
Analysis of functional connectivity networks (FCNs) derived from resting-state functional magnetic resonance imaging (rs-fMRI) has greatly advanced our understanding of brain diseases, including Alzheimer's disease (AD) and attention deficit hyperact...
Pathological Asymmetry-Guided Progressive Learning for Acute Ischemic Stroke Infarct Segmentation.
IEEE transactions on medical imaging
Dec 2, 2024
Quantitative infarct estimation is crucial for diagnosis, treatment and prognosis in acute ischemic stroke (AIS) patients. As the early changes of ischemic tissue are subtle and easily confounded by normal brain tissue, it remains a very challenging ...
Hybrid Network Using Dynamic Graph Convolution and Temporal Self-Attention for EEG-Based Emotion Recognition.
IEEE transactions on neural networks and learning systems
Dec 2, 2024
The electroencephalogram (EEG) signal has become a highly effective decoding target for emotion recognition and has garnered significant attention from researchers. Its spatial topological and time-dependent characteristics make it crucial to explore...
Medical Transformer: Universal Encoder for 3-D Brain MRI Analysis.
IEEE transactions on neural networks and learning systems
Dec 2, 2024
Transfer learning has attracted considerable attention in medical image analysis because of the limited number of annotated 3-D medical datasets available for training data-driven deep learning models in the real world. We propose Medical Transformer...
Site-Invariant Meta-Modulation Learning for Multisite Autism Spectrum Disorders Diagnosis.
IEEE transactions on neural networks and learning systems
Dec 2, 2024
Large amounts of fMRI data are essential to building generalized predictive models for brain disease diagnosis. In order to conduct extensive data analysis, it is often necessary to gather data from multiple organizations. However, the site variation...
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