AIMC Topic: Brain

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Orthogonal Mixed-Effects Modeling for High-Dimensional Longitudinal Data: An Unsupervised Learning Approach.

IEEE transactions on medical imaging Jan 2, 2025
The linear mixed-effects model is commonly utilized to interpret longitudinal data, characterizing both the global longitudinal trajectory across all observations and longitudinal trajectories within individuals. However, characterizing these traject...
Image Processing, Computer-Assisted Longitudinal Studies Magnetic Resonance Imaging Brain Female Male Unsupervised Machine Learning Alzheimer Disease Image Interpretation, Computer-Assisted Humans Algorithms
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Multi-Modal Diagnosis of Alzheimer's Disease Using Interpretable Graph Convolutional Networks.

IEEE transactions on medical imaging Jan 2, 2025
The interconnection between brain regions in neurological disease encodes vital information for the advancement of biomarkers and diagnostics. Although graph convolutional networks are widely applied for discovering brain connection patterns that poi...
Humans Neural Networks, Computer Databases, Factual Brain Cognitive Dysfunction Female Alzheimer Disease Magnetic Resonance Imaging Aged Image Interpretation, Computer-Assisted Multimodal Imaging Male Neuroimaging
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Generalizable Reconstruction for Accelerating MR Imaging via Federated Learning With Neural Architecture Search.

IEEE transactions on medical imaging Jan 2, 2025
Heterogeneous data captured by different scanning devices and imaging protocols can affect the generalization performance of the deep learning magnetic resonance (MR) reconstruction model. While a centralized training model is effective in mitigating...
Federated Learning Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Algorithms Brain Humans Neural Networks, Computer
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Unsupervised Domain Adaptation for EM Image Denoising With Invertible Networks.

IEEE transactions on medical imaging Jan 2, 2025
Electron microscopy (EM) image denoising is critical for visualization and subsequent analysis. Despite the remarkable achievements of deep learning-based non-blind denoising methods, their performance drops significantly when domain shifts exist bet...
Humans Algorithms Image Processing, Computer-Assisted Brain Mice Unsupervised Machine Learning Animals Deep Learning Signal-To-Noise Ratio
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Deep learning predicts DNA methylation regulatory variants in specific brain cell types and enhances fine mapping for brain disorders.

Science advances Jan 1, 2025
DNA methylation (DNAm) is essential for brain development and function and potentially mediates the effects of genetic risk variants underlying brain disorders. We present INTERACT, a transformer-based deep learning model to predict regulatory varian...
Models, Biological Alzheimer Disease CpG Islands Nucleotide Motifs Inheritance Patterns Genetic Predisposition to Disease Transcription Factors DNA Methylation Male Deep Learning Genome-Wide Association Study Young Adult Adult Humans Brain
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WALINET: A water and lipid identification convolutional neural network for nuisance signal removal in MR spectroscopic imaging.

Magnetic resonance in medicine Dec 31, 2024
PURPOSE: Proton magnetic resonance spectroscopic imaging ( -MRSI) provides noninvasive spectral-spatial mapping of metabolism. However, long-standing problems in whole-brain -MRSI are spectral overlap of metabolite peaks with large lipid signal fro...
Humans Neural Networks, Computer Female Adult Algorithms Brain Lipids Water Magnetic Resonance Spectroscopy Male Image Processing, Computer-Assisted Proton Magnetic Resonance Spectroscopy Deep Learning Magnetic Resonance Imaging Convolutional Neural Networks
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A Novel State Space Model with Dynamic Graphic Neural Network for EEG Event Detection.

International journal of neural systems Dec 31, 2024
Electroencephalography (EEG) is a widely used physiological signal to obtain information of brain activity, and its automatic detection holds significant research importance, which saves doctors' time, improves detection efficiency and accuracy. Howe...
Brain Electroencephalography Sleep Stages Humans Seizures Neural Networks, Computer Signal Processing, Computer-Assisted
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A computational deep learning investigation of animacy perception in the human brain.

Communications biology Dec 31, 2024
The functional organization of the human object vision pathway distinguishes between animate and inanimate objects. To understand animacy perception, we explore the case of zoomorphic objects resembling animals. While the perception of these objects ...
Visual Perception Brain Humans Animals Neural Networks, Computer Deep Learning
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Biologically plausible gated recurrent neural networks for working memory and learning-to-learn.

PloS one Dec 31, 2024
The acquisition of knowledge and skills does not occur in isolation but learning experiences amalgamate within and across domains. The process through which learning can accelerate over time is referred to as learning-to-learn or meta-learning. While...
Animals Models, Neurological Humans Memory, Short-Term Nerve Net Neural Networks, Computer Brain Learning
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Healthy core: Harmonizing brain MRI for supporting multicenter migraine classification studies.

PloS one Dec 31, 2024
Multicenter and multi-scanner imaging studies may be necessary to ensure sufficiently large sample sizes for developing accurate predictive models. However, multicenter studies, incorporating varying research participant characteristics, MRI scanners...
Middle Aged Female Case-Control Studies Humans Migraine Disorders Adult Magnetic Resonance Imaging Machine Learning Male Multicenter Studies as Topic Brain
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