AIMC Topic: Brain

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Neuromorphic engineering: Artificial brains for artificial intelligence.

Annals of the New York Academy of Sciences Nov 20, 2024
Neuromorphic engineering is a research discipline that tries to bridge the gaps between neuroscience and engineering, cognition and algorithms, and natural and artificial intelligence. Neuromorphic engineering promises revolutionary breakthroughs tha...
Humans Neural Networks, Computer Artificial Intelligence Algorithms Brain Neurosciences Cognition
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Blip-up blip-down circular EPI (BUDA-cEPI) for distortion-free dMRI with rapid unrolled deep learning reconstruction.

Magnetic resonance imaging Nov 19, 2024
PURPOSE: BUDA-cEPI has been shown to achieve high-quality, high-resolution diffusion magnetic resonance imaging (dMRI) with fast acquisition time, particularly when used in conjunction with S-LORAKS reconstruction. However, this comes at a cost of mo...
Diffusion Magnetic Resonance Imaging Echo-Planar Imaging Brain Deep Learning Image Processing, Computer-Assisted Humans Neural Networks, Computer Algorithms
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Enhancing Motor Imagery Classification with Residual Graph Convolutional Networks and Multi-Feature Fusion.

International journal of neural systems Nov 19, 2024
Stroke, an abrupt cerebrovascular ailment resulting in brain tissue damage, has prompted the adoption of motor imagery (MI)-based brain-computer interface (BCI) systems in stroke rehabilitation. However, analyzing electroencephalogram (EEG) signals f...
Aged Adult Male Middle Aged Neural Networks, Computer Brain Female Brain-Computer Interfaces Stroke Rehabilitation Imagination Electroencephalography Signal Processing, Computer-Assisted Stroke Humans
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Deep Learning Recognition of Paroxysmal Kinesigenic Dyskinesia Based on EEG Functional Connectivity.

International journal of neural systems Nov 19, 2024
Paroxysmal kinesigenic dyskinesia (PKD) is a rare neurological disorder marked by transient involuntary movements triggered by sudden actions. Current diagnostic approaches, including genetic screening, face challenges in identifying secondary cases ...
Humans Electroencephalography Adult Nerve Net Dystonia Male Theta Rhythm Deep Learning Adolescent Brain Female Young Adult
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Multiclass classification of Alzheimer's disease prodromal stages using sequential feature embeddings and regularized multikernel support vector machine.

NeuroImage Nov 19, 2024
The detection of patients in the cognitive normal (CN), mild cognitive impairment (MCI), and Alzheimer's disease (AD) stages of neurodegeneration is crucial for early treatment interventions. However, the heterogeneity of MCI data samples poses a cha...
Brain Prodromal Symptoms Male Alzheimer Disease Humans Female Cognitive Dysfunction Positron-Emission Tomography Support Vector Machine Aged Image Interpretation, Computer-Assisted Magnetic Resonance Imaging
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A Novel and Powerful Dual-Stream Multi-Level Graph Convolution Network for Emotion Recognition.

Sensors (Basel, Switzerland) Nov 19, 2024
Emotion recognition enables machines to more acutely perceive and understand users' emotional states, thereby offering more personalized and natural interactive experiences. Given the regularity of the responses of brain activity to human cognitive p...
Brain Humans Emotions Neural Networks, Computer Electroencephalography Algorithms
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Using machine learning to develop a stacking ensemble learning model for the CT radiomics classification of brain metastases.

Scientific reports Nov 19, 2024
The objective of this study was to explore the potential of machine-learning techniques in the automatic identification and classification of brain metastases from a radiomic perspective, aiming to improve the accuracy of tumor volume assessment for ...
Machine Learning Algorithms Brain Tomography, X-Ray Computed Female Aged Radiomics Humans Neural Networks, Computer Support Vector Machine Brain Neoplasms Tumor Burden Male Middle Aged
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A combined model integrating radiomics and deep learning based on multiparametric magnetic resonance imaging for classification of brain metastases.

Acta radiologica (Stockholm, Sweden : 1987) Nov 18, 2024
BACKGROUND: Radiomics and deep learning (DL) can individually and efficiently identify the pathological type of brain metastases (BMs).
Radiomics Brain Neoplasms Male Middle Aged Female Aged Adult Feasibility Studies Image Interpretation, Computer-Assisted Adenocarcinoma of Lung Multiparametric Magnetic Resonance Imaging Deep Learning Lung Neoplasms Magnetic Resonance Imaging Humans Brain Retrospective Studies
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GraFMRI: A graph-based fusion framework for robust multi-modal MRI reconstruction.

Magnetic resonance imaging Nov 17, 2024
PURPOSE: This study introduces GraFMRI, a novel framework designed to address the challenges of reconstructing high-quality MRI images from undersampled k-space data. Traditional methods often suffer from noise amplification and loss of structural de...
Algorithms Humans Brain Neural Networks, Computer Image Processing, Computer-Assisted Magnetic Resonance Imaging Multimodal Imaging Artifacts Signal-To-Noise Ratio
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Recognition of autism in subcortical brain volumetric images using autoencoding-based region selection method and Siamese Convolutional Neural Network.

International journal of medical informatics Nov 16, 2024
BACKGROUND: Autism Spectrum Disorder (ASD) is a neurodevelopmental condition that affects social interactions and behavior. Accurate and early diagnosis of ASD is still challenging even with the improvements in neuroimaging technology and machine lea...
Adolescent Child Imaging, Three-Dimensional Magnetic Resonance Imaging Autistic Disorder Neuroimaging Autism Spectrum Disorder Brain Female Male Humans Neural Networks, Computer Algorithms
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