Neurology

Latest AI and machine learning research in neurology for healthcare professionals.

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Enhanced choroid plexus segmentation with 3D UX-Net and its association with disease progression in multiple sclerosis.

BACKGROUND: The choroid plexus (CP) is suggested to be closely associated with the neuroinflammation...

An rs-fMRI based neuroimaging marker for adult absence epilepsy.

OBJECTIVE: Approximately 20-30 % of epilepsy patients exhibit negative findings on routine magnetic ...

Predicting Therapeutic Response to Hypoglossal Nerve Stimulation Using Deep Learning.

OBJECTIVES: To develop and validate machine learning (ML) and deep learning (DL) models using drug-i...

Eye-tracker and fNIRS: Using neuroscientific tools to assess the learning experience during children's educational robotics activities.

In technology education, there has been a paradigmatic shift towards student-centered approaches suc...

NeurostimML: a machine learning model for predicting neurostimulation-induced tissue damage.

. The safe delivery of electrical current to neural tissue depends on many factors, yet previous met...

Identification of endoplasmic reticulum stress genes in human stroke based on bioinformatics and machine learning.

After ischemic stroke (IS), secondary injury is intimately linked to endoplasmic reticulum (ER) stre...

Feature evaluation for myoelectric pattern recognition of multiple nearby reaching targets.

Intention detection of the reaching movement is considerable for myoelectric human and machine colla...

Artificial intelligence for neuro MRI acquisition: a review.

OBJECT: To review recent advances of artificial intelligence (AI) in enhancing the efficiency and th...

A machine learning model predicts stroke associated with blood cadmium level.

Stroke is the leading cause of death and disability worldwide. Cadmium is a prevalent environmental ...

When performing actions with robots, attribution of intentionality affects the sense of joint agency.

Sense of joint agency (SoJA) is the sense of control experienced by humans when acting with others t...

Characterizing Disease Progression in Parkinson's Disease from Videos of the Finger Tapping Test.

INTRODUCTION: Parkinson's disease (PD) is characterized by motor symptoms whose progression is typic...

Multi-grained contrastive representation learning for label-efficient lesion segmentation and onset time classification of acute ischemic stroke.

Ischemic lesion segmentation and the time since stroke (TSS) onset classification from paired multi-...

Prediction of Alzheimer's disease progression within 6 years using speech: A novel approach leveraging language models.

INTRODUCTION: Identification of individuals with mild cognitive impairment (MCI) who are at risk of ...

BAOS-CNN: A novel deep neuroevolution algorithm for multispecies seagrass detection.

Deep learning, a subset of machine learning that utilizes neural networks, has seen significant adva...

EMG-based prediction of step direction for a better control of lower limb wearable devices.

BACKGROUND AND OBJECTIVES: Lower-limb wearable devices can significantly improve the quality of life...

Assessing gait dysfunction severity in Parkinson's Disease using 2-Stream Spatial-Temporal Neural Network.

Parkinson's Disease (PD), a neurodegenerative disorder, significantly impacts the quality of life fo...

An interpretable machine learning-based cerebrospinal fluid proteomics clock for predicting age reveals novel insights into brain aging.

Machine learning can be used to create "biologic clocks" that predict age. However, organs, tissues,...

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