AIMC Topic: Brain

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Predicting the effectiveness of binaural beats on working memory.

Neuroreport Sep 30, 2024
Working memory is vital for short-term information processing. Binaural beats can enhance working memory by improving attention and memory consolidation through neural synchronization. However, individual differences in cognitive and neuronal functio...
Auditory Perception Male Electroencephalography Memory, Short-Term Attention Humans Female Acoustic Stimulation Machine Learning Young Adult Brain Waves Brain Adult
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MMF-NNs: Multi-modal Multi-granularity Fusion Neural Networks for brain networks and its application to epilepsy identification.

Artificial intelligence in medicine Sep 30, 2024
Structural and functional brain networks are generated from two scan sequences of magnetic resonance imaging data, which can provide different perspectives for describing pathological changes caused by brain diseases. Recent studies found that fusing...
Brain Humans Nerve Net Magnetic Resonance Imaging Neural Networks, Computer Epilepsy
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Joint self-supervised and supervised contrastive learning for multimodal MRI data: Towards predicting abnormal neurodevelopment.

Artificial intelligence in medicine Sep 30, 2024
The integration of different imaging modalities, such as structural, diffusion tensor, and functional magnetic resonance imaging, with deep learning models has yielded promising outcomes in discerning phenotypic characteristics and enhancing disease ...
Supervised Machine Learning Diagnosis, Computer-Assisted Humans Image Interpretation, Computer-Assisted Deep Learning Brain Magnetic Resonance Imaging Neurodevelopmental Disorders Multimodal Imaging
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Classification of mindfulness experiences from gamma-band effective connectivity: Application of machine-learning algorithms on resting, breathing, and body scan.

Computer methods and programs in biomedicine Sep 28, 2024
BACKGROUND AND OBJECTIVE: Practicing mindfulness is a mental process toward interoceptive awareness, achieving stress reduction and emotion regulation through brain-function alteration. Literature has shown that electroencephalography (EEG)-derived c...
Brain Female Young Adult Adult Male Stress, Psychological Humans Rest Machine Learning Algorithms Respiration Support Vector Machine Mindfulness Bayes Theorem Electroencephalography
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MGA-Net: A novel mask-guided attention neural network for precision neonatal brain imaging.

NeuroImage Sep 28, 2024
In this study, we introduce MGA-Net, a novel mask-guided attention neural network, which extends the U-net model for precision neonatal brain imaging. MGA-Net is designed to extract the brain from other structures and reconstruct high-quality brain i...
Infant, Newborn Male Image Processing, Computer-Assisted Neural Networks, Computer Brain Female Magnetic Resonance Imaging Neuroimaging Humans
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Translational Connectomics: overview of machine learning in macroscale Connectomics for clinical insights.

BMC neurology Sep 28, 2024
Connectomics is a neuroscience paradigm focused on noninvasively mapping highly intricate and organized networks of neurons. The advent of neuroimaging has led to extensive mapping of the brain functional and structural connectome on a macroscale lev...
Machine Learning Brain Translational Research, Biomedical Neuroimaging Humans Connectome
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Label refinement network from synthetic error augmentation for medical image segmentation.

Medical image analysis Sep 27, 2024
Deep convolutional neural networks for image segmentation do not learn the label structure explicitly and may produce segmentations with an incorrect structure, e.g., with disconnected cylindrical structures in the segmentation of tree-like structure...
Radiography, Thoracic Computed Tomography Angiography Humans Neural Networks, Computer Algorithms Imaging, Three-Dimensional Brain Image Processing, Computer-Assisted Tomography, X-Ray Computed
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A Flow-based Truncated Denoising Diffusion Model for super-resolution Magnetic Resonance Spectroscopic Imaging.

Medical image analysis Sep 27, 2024
Magnetic Resonance Spectroscopic Imaging (MRSI) is a non-invasive imaging technique for studying metabolism and has become a crucial tool for understanding neurological diseases, cancers and diabetes. High spatial resolution MRSI is needed to charact...
Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Signal-To-Noise Ratio Magnetic Resonance Spectroscopy Algorithms Brain Brain Neoplasms Humans
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Impact of a deep learning-based brain CT interpretation algorithm on clinical decision-making for intracranial hemorrhage in the emergency department.

Scientific reports Sep 27, 2024
Intracranial hemorrhage is a critical emergency that requires prompt and accurate diagnosis in the emergency department (ED). Deep learning technology can assist in interpreting non-enhanced brain CT scans, but its real-world impact on clinical decis...
Emergency Service, Hospital Intracranial Hemorrhages Female Brain Adult Male Tomography, X-Ray Computed Sensitivity and Specificity Deep Learning Clinical Decision-Making Humans ROC Curve Algorithms
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Identification of Bipolar Disorder and Schizophrenia Based on Brain CT and Deep Learning Methods.

Journal of imaging informatics in medicine Sep 26, 2024
With the increasing prevalence of mental illness, accurate clinical diagnosis of mental illness is crucial. Compared with MRI, CT has the advantages of wide application, low price, short scanning time, and high patient cooperation. This study aims to...
Brain Tomography, X-Ray Computed Female Humans Case-Control Studies Adult Bipolar Disorder Deep Learning Schizophrenia Male Middle Aged
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