AIMC Topic: Brain

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Identifying autism spectrum disorder based on machine learning for multi-site fMRI.

Journal of neuroscience methods Jan 26, 2025
BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by repetitive stereotypical behavior and social impairment. Early diagnosis is essential for developing a treatment plan for autism. Although multi-site data ca...
Male Child Autism Spectrum Disorder Magnetic Resonance Imaging Humans Brain Machine Learning Female
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Research on noise-induced hearing loss based on functional and structural MRI using machine learning methods.

Scientific reports Jan 26, 2025
Noise-induced hearing loss (NIHL) is a common occupational condition. The aim of this study was to develop a classification model for NIHL on the basis of both functional magnetic resonance imaging (fMRI) and structural magnetic resonance imaging (sM...
Middle Aged ROC Curve Support Vector Machine Female Adult Male Humans Magnetic Resonance Imaging Machine Learning Gray Matter Brain Hearing Loss, Noise-Induced
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Age group classification based on optical measurement of brain pulsation using machine learning.

Scientific reports Jan 25, 2025
Optical techniques, such as functional near-infrared spectroscopy (fNIRS), contain high potential for the development of non-invasive wearable systems for evaluating cerebral vascular condition in aging, due to their portability and ability to monito...
Aging Middle Aged Spectroscopy, Near-Infrared Support Vector Machine Age Factors Humans Magnetic Resonance Imaging Machine Learning Cerebrovascular Circulation Young Adult Female Brain Adult Aged Male
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The intelligent brain and the energy heart: Synergistic evolution of artificial intelligence and energy storage technology in China.

Acta psychologica Jan 23, 2025
In the context of China's ongoing industrial revolution and technological transformation, there is a growing demand for advanced energy management solutions and the increasing role of artificial intelligence in various industries. This paper aims to ...
China Intelligence Humans Artificial Intelligence Brain
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A joint three-plane physics-constrained deep learning based polynomial fitting approach for MR electrical properties tomography.

NeuroImage Jan 23, 2025
Magnetic resonance electrical properties tomography can extract the electrical properties of in-vivo tissue. To estimate tissue electrical properties, various reconstruction algorithms have been proposed. However, physics-based reconstructions are pr...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Algorithms Tomography Humans Brain Neural Networks, Computer Deep Learning
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Mapping the topography of spatial gene expression with interpretable deep learning.

Nature methods Jan 23, 2025
Spatially resolved transcriptomics technologies provide high-throughput measurements of gene expression in a tissue slice, but the sparsity of these data complicates analysis of spatial gene expression patterns. We address this issue by deriving a to...
Mice Brain Tumor Microenvironment Animals Gene Expression Profiling Transcriptome Deep Learning Humans Neural Networks, Computer Algorithms
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The 'Sandwich' meta-framework for architecture agnostic deep privacy-preserving transfer learning for non-invasive brainwave decoding.

Journal of neural engineering Jan 23, 2025
. Machine learning has enhanced the performance of decoding signals indicating human behaviour. Electroencephalography (EEG) brainwave decoding, as an exemplar indicating neural activity and human thoughts non-invasively, has been helpful in neural a...
Humans Neural Networks, Computer Machine Learning Privacy Brain-Computer Interfaces Brain Waves Brain Deep Learning Electroencephalography
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A novel hybrid ViT-LSTM model with explainable AI for brain stroke detection and classification in CT images: A case study of Rajshahi region.

Computers in biology and medicine Jan 22, 2025
Computed tomography (CT) scans play a key role in the diagnosis of stroke, a leading cause of morbidity and mortality worldwide. However, interpreting these scans is often challenging, necessitating automated solutions for timely and accurate diagnos...
Artificial Intelligence Brain Tomography, X-Ray Computed Humans Neural Networks, Computer Stroke
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Eeg Microstates and Balance Parameters for Stroke Discrimination: A Machine Learning Approach.

Brain topography Jan 22, 2025
Electroencephalography microstates (EEG-MS) show promise to be a neurobiological biomarker in stroke. Thus, the aim of the study was to identify biomarkers to discriminate stroke patients from healthy individuals based on EEG-MS and clinical features...
Brain Female Aged Humans Machine Learning Electroencephalography Stroke Adult Male Middle Aged
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A comparative machine learning study of schizophrenia biomarkers derived from functional connectivity.

Scientific reports Jan 22, 2025
Functional connectivity holds promise as a biomarker of schizophrenia. Yet, the high dimensionality of predictive models trained on functional connectomes, combined with small sample sizes in clinical research, increases the risk of overfitting. Rece...
Magnetic Resonance Imaging Schizophrenia Connectome Machine Learning Biomarkers Brain Female Adult Humans Male
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