AIMC Topic: Brain
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Brain CT image classification based on mask RCNN and attention mechanism.
Scientific reports
Nov 26, 2024
Along with the computer application technology progress, machine learning, and block-chain techniques have been applied comprehensively in various fields. The application of machine learning, and block-chain techniques into medical image retrieval, c...
Effective Alzheimer's disease detection using enhanced Xception blending with snapshot ensemble.
Scientific reports
Nov 26, 2024
Alzheimer's disease (AD), a prevalent neurodegenerative disorder, leads to progressive dementia, which impairs decision-making, problem-solving, and communication. While there is no cure, early detection can facilitate treatments to slow its progress...
Altered Blood Oxygen Level-Dependent Signal Stability in the Brain of Patients with Major Depressive Disorder Undergoing Resting-State Functional Magnetic Resonance Imaging.
Neuropsychobiology
Nov 26, 2024
INTRODUCTION: Major depressive disorder (MDD) is a common, relapse-prone psychiatric disorder with unknown pathogenesis. Previous studies on resting-state functional magnetic resonance imaging of MDD have mostly focused on the spontaneous activity of...
Single-channel electroencephalography decomposition by detector-atom network and its pre-trained model.
Journal of neuroscience methods
Nov 23, 2024
Signal decomposition techniques utilizing multi-channel spatial features are critical for analyzing, denoising, and classifying electroencephalography (EEG) signals. To facilitate the decomposition of signals recorded with limited channels, this pape...
Neural correlates of empathy in donation decisions: Insights from EEG and machine learning.
Neuroscience
Nov 23, 2024
Empathy is central to individual and societal well-being. Numerous studies have examined how trait of empathy affects prosocial behavior. However, little studies explored the psychological and neural mechanisms by which different dimensions of trait ...
Multi-task magnetic resonance imaging reconstruction using meta-learning.
Magnetic resonance imaging
Nov 22, 2024
Using single-task deep learning methods to reconstruct Magnetic Resonance Imaging (MRI) data acquired with different imaging sequences is inherently challenging. The trained deep learning model typically lacks generalizability, and the dissimilarity ...
Multi-scale multimodal deep learning framework for Alzheimer's disease diagnosis.
Computers in biology and medicine
Nov 22, 2024
Multimodal neuroimaging data, including magnetic resonance imaging (MRI) and positron emission tomography (PET), provides complementary information about the brain that can aid in Alzheimer's disease (AD) diagnosis. However, most existing deep learni...
A novel approach for brain connectivity using recurrent neural networks and integrated gradients.
Computers in biology and medicine
Nov 21, 2024
Brain connectivity is an important tool for understanding the cognitive and perceptive neural mechanisms in the neuroimaging field. Many methods for estimating effective connectivity have relied on the linear regressive model. However, the linear reg...
A Deep Dynamic Causal Learning Model to Study Changes in Dynamic Effective Connectivity During Brain Development.
IEEE transactions on bio-medical engineering
Nov 21, 2024
OBJECTIVE: Brain dynamic effective connectivity (dEC), characterizes the information transmission patterns between brain regions that change over time, which provides insight into the biological mechanism underlying brain development. However, most e...
Boosted Harris Hawks Shuffled Shepherd Optimization Augmented Deep Learning based motor imagery classification for brain computer interface.
PloS one
Nov 21, 2024
Motor imagery (MI) classification has been commonly employed in making brain-computer interfaces (BCI) to manage the outside tools as a substitute neural muscular path. Effectual MI classification in BCI improves communication and mobility for people...
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