AIMC Topic: Brain
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Machine learning-based prognostic prediction for acute ischemic stroke using whole-brain and infarct multi-PLD ASL radiomics.
BMC medical imaging
Jul 4, 2025
INTRODUCTION: Accurate early prognostic prediction for acute ischemic stroke (AIS) is essential for guiding personalized treatment. This study aimed to assess the predictive value of radiomics features from whole-brain and infarct cerebral blood flow...
3BTRON: A Blood-Brain Barrier Recognition Network.
Communications biology
Jul 4, 2025
The blood-brain barrier (BBB) plays a crucial role in maintaining brain homeostasis. During ageing, the BBB undergoes structural alterations. Electron microscopy (EM) is the gold standard for studying the structural alterations of the brain vasculatu...
Intrinsic dynamic shapes responses to external stimulation in the human brain.
eLife
Jul 3, 2025
Sensory stimulation of the brain reverberates in its recurrent neural networks. However, current computational models of brain activity do not separate immediate sensory responses from this intrinsic dynamic. We apply a vector-autoregressive model wi...
Influence of cognitive networks and task performance on fMRI-based state classification using DNN models.
Scientific reports
Jul 3, 2025
Deep neural networks (DNNs) excel at extracting insights from complex data across various fields, however, their application in cognitive neuroscience remains limited, largely due to the lack of approaches with interpretability. Here, we employ two d...
Universal dimensions of visual representation.
Science advances
Jul 2, 2025
Do visual neural networks learn brain-aligned representations because they share architectural constraints and task objectives with biological vision or because they share universal features of natural image processing? We characterized the universal...
A dual path graph neural network framework for dementia diagnosis.
Scientific reports
Jul 2, 2025
Dementia typically results from damage to neural pathways and the consequent degeneration of neuronal connections. Graph neural networks (GNNs) have been widely employed to model complex brain networks. However, leveraging the complementary temporal,...
Scalable geometric learning with correlation-based functional brain networks.
Scientific reports
Jul 2, 2025
Correlation matrices serve as fundamental representations of functional brain networks in neuroimaging. Conventional analyses often treat pairwise interactions independently within Euclidean space, neglecting the underlying geometry of correlation st...
A novel neuroimaging based early detection framework for alzheimer disease using deep learning.
Scientific reports
Jul 2, 2025
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that significantly impacts cognitive function, posing a major global health challenge. Despite its rising prevalence, particularly in low and middle-income countries, early diagnosi...
Classifying and diagnosing Alzheimer's disease with deep learning using 6735 brain MRI images.
Scientific reports
Jul 2, 2025
Traditional diagnostic methods for Alzheimer's disease often suffer from low accuracy and lengthy processing times, delaying crucial interventions and patient care. Deep convolutional neural networks trained on MRI data can enhance diagnostic precisi...
Accelerating brain T2-weighted imaging using artificial intelligence-assisted compressed sensing combined with deep learning-based reconstruction: a feasibility study at 5.0T MRI.
BMC medical imaging
Jul 1, 2025
BACKGROUND: T2-weighted imaging (T2WI), renowned for its sensitivity to edema and lesions, faces clinical limitations due to prolonged scanning time, increasing patient discomfort, and motion artifacts. The individual applications of artificial intel...
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