AIMC Topic: Brain
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Alterations in dynamic regional homogeneity within default mode network in patients with thyroid-associated ophthalmopathy.
Neuroreport
Jun 1, 2024
Thyroid-associated ophthalmopathy (TAO) is a significant autoimmune eye disease known for causing exophthalmos and substantial optic nerve damage. Prior investigations have solely focused on static functional MRI (fMRI) scans of the brain in TAO pati...
EEG based functional connectivity in resting and emotional states may identify major depressive disorder using machine learning.
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Jun 1, 2024
OBJECTIVE: Disrupted brain network connectivity underlies major depressive disorder (MDD). Altered EEG based Functional connectivity (FC) with Emotional stimuli in major depressive disorder (MDD) in addition to resting state FC may help in improving ...
SIMS: A deep-learning label transfer tool for single-cell RNA sequencing analysis.
Cell genomics
May 31, 2024
Cell atlases serve as vital references for automating cell labeling in new samples, yet existing classification algorithms struggle with accuracy. Here we introduce SIMS (scalable, interpretable machine learning for single cell), a low-code data-effi...
Enhancing classification accuracy of HRF signals in fNIRS using semi-supervised learning and filtering.
Progress in brain research
May 31, 2024
This paper introduces a novel approach to enhance the classification accuracy of hemodynamic response function (HRF) signals acquired through functional near-infrared spectroscopy (fNIRS). Leveraging a semi-supervised learning (SSL) framework alongsi...
Classifying Routine Clinical Electroencephalograms With Multivariate Iterative Filtering and Convolutional Neural Networks.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
May 31, 2024
Electroencephalogram (EEG) is widely used in basic and clinical neuroscience to explore neural states in various populations, and classifying these EEG recordings is a fundamental challenge. While machine learning shows promising results in classifyi...
CT-Net: an interpretable CNN-Transformer fusion network for fNIRS classification.
Medical & biological engineering & computing
May 30, 2024
Functional near-infrared spectroscopy (fNIRS), an optical neuroimaging technique, has been widely used in the field of brain activity recognition and brain-computer interface. Existing works have proposed deep learning-based algorithms for the fNIRS ...
Generalizing the Enhanced-Deep-Super-Resolution Neural Network to Brain MR Images: A Retrospective Study on the Cam-CAN Dataset.
eNeuro
May 30, 2024
The Enhanced-Deep-Super-Resolution (EDSR) model is a state-of-the-art convolutional neural network suitable for improving image spatial resolution. It was previously trained with general-purpose pictures and then, in this work, tested on biomedical m...
Multimodal Brain Tumor Classification Using Convolutional Tumnet Architecture.
Behavioural neurology
May 30, 2024
The most common and aggressive tumor is brain malignancy, which has a short life span in the fourth grade of the disease. As a result, the medical plan may be a crucial step toward improving the well-being of a patient. Both diagnosis and therapy are...
Deep-learning-based motion correction using multichannel MRI data: a study using simulated artifacts in the fastMRI dataset.
NMR in biomedicine
May 29, 2024
Deep learning presents a generalizable solution for motion correction requiring no pulse sequence modifications or additional hardware, but previous networks have all been applied to coil-combined data. Multichannel MRI data provide a degree of spati...
Practical measurements distinguishing physiological and pathological stereoelectroencephalography channels based on high-frequency oscillations in the human brain.
Epilepsia open
May 29, 2024
OBJECTIVE: The present study aimed to identify various distinguishing features for use in the accurate classification of stereoelectroencephalography (SEEG) channels based on high-frequency oscillations (HFOs) inside and outside the epileptogenic zon...
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