AIMC Topic: Brain

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Machine Learning Approaches to Identify Affected Brain Regions in Movement Disorders Using MRI Data: A Systematic Review and Diagnostic Meta-analysis.

Journal of magnetic resonance imaging : JMRI Mar 27, 2024
BACKGROUND: Movement disorders such as Parkinson's disease are associated with structural and functional changes in specific brain regions. Advanced magnetic resonance imaging (MRI) techniques combined with machine learning (ML) are promising tools f...
Diffusion Tensor Imaging Movement Disorders Humans Machine Learning Brain Sensitivity and Specificity Magnetic Resonance Imaging
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Employing deep learning and transfer learning for accurate brain tumor detection.

Scientific reports Mar 27, 2024
Artificial intelligence-powered deep learning methods are being used to diagnose brain tumors with high accuracy, owing to their ability to process large amounts of data. Magnetic resonance imaging stands as the gold standard for brain tumor diagnosi...
Meningeal Neoplasms Brain Brain Neoplasms Deep Learning Humans Artificial Intelligence Machine Learning
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Combined brain topological metrics with machine learning to distinguish essential tremor and tremor-dominant Parkinson's disease.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology Mar 25, 2024
BACKGROUND: Essential tremor (ET) and Parkinson's disease (PD) are the two most prevalent movement disorders, sharing several overlapping tremor clinical features. Although growing evidence pointed out that changes in similar brain network nodes are ...
Diagnosis, Differential Essential Tremor Machine Learning Brain Female Humans Support Vector Machine Magnetic Resonance Imaging Parkinson Disease Aged Male Middle Aged
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A review of self-supervised, generative, and few-shot deep learning methods for data-limited magnetic resonance imaging segmentation.

NMR in biomedicine Mar 24, 2024
Magnetic resonance imaging (MRI) is a ubiquitous medical imaging technology with applications in disease diagnostics, intervention, and treatment planning. Accurate MRI segmentation is critical for diagnosing abnormalities, monitoring diseases, and d...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Supervised Machine Learning Algorithms Brain Deep Learning Humans
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Applying Common Spatial Pattern and Convolutional Neural Network to Classify Movements via EEG Signals.

Clinical EEG and neuroscience Mar 24, 2024
Developing an electroencephalography (EEG)-based brain-computer interface (BCI) system is crucial to enhancing the control of external prostheses by accurately distinguishing various movements through brain signals. This innovation can provide comfor...
Humans Neural Networks, Computer Algorithms Signal Processing, Computer-Assisted Wrist Brain-Computer Interfaces Movement Adult Male Electroencephalography Brain Female Young Adult
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Deep Learning Accelerated Brain Diffusion-Weighted MRI with Super Resolution Processing.

Academic radiology Mar 22, 2024
OBJECTIVES: To investigate the clinical feasibility and image quality of accelerated brain diffusion-weighted imaging (DWI) with deep learning image reconstruction and super resolution.
Diffusion Magnetic Resonance Imaging Middle Aged Deep Learning Image Processing, Computer-Assisted Feasibility Studies Image Interpretation, Computer-Assisted Brain Diseases Young Adult Adult Male Female Aged Aged, 80 and over Prospective Studies Brain Humans
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Active Learning in Brain Tumor Segmentation with Uncertainty Sampling and Annotation Redundancy Restriction.

Journal of imaging informatics in medicine Mar 21, 2024
Deep learning models have demonstrated great potential in medical imaging but are limited by the expensive, large volume of annotations required. To address this, we compared different active learning strategies by training models on subsets of the m...
Brain Neoplasms Deep Learning Image Processing, Computer-Assisted Humans Brain Magnetic Resonance Imaging Bayes Theorem Uncertainty
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A number sense as an emergent property of the manipulating brain.

Scientific reports Mar 21, 2024
The ability to understand and manipulate numbers and quantities emerges during childhood, but the mechanism through which humans acquire and develop this ability is still poorly understood. We explore this question through a model, assuming that the ...
Brain Learning Cognition Humans Artificial Intelligence Visual Perception
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Diagnosing schizophrenia using deep learning: Novel interpretation approaches and multi-site validation.

Brain research Mar 20, 2024
Schizophrenia is a profound and enduring mental disorder that imposes significant negative impacts on individuals, their families, and society at large. The development of more accurate and objective diagnostic tools for schizophrenia can be expedite...
Schizophrenia Reproducibility of Results Adult Male Middle Aged Deep Learning Magnetic Resonance Imaging Humans Brain Female
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eDeeplepsy: An artificial neural framework to reveal different brain states in children with epileptic spasms.

Epilepsy & behavior : E&B Mar 20, 2024
OBJECTIVE: Despite advances, analysis and interpretation of EEG still essentially rely on visual inspection by a super-specialized physician. Considering the vast amount of data that composes the EEG, much of the detail inevitably escapes ordinary hu...
Brain Female Male Humans Neural Networks, Computer Child, Preschool Child Electroencephalography Epilepsy Infant Deep Learning Adolescent
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