Neurology

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

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Combining MRI radiomics and clinical features for early identification of drug-resistant epilepsy in people with newly diagnosed epilepsy.

OBJECTIVE: To identify newly diagnosed patients with drug-resistant epilepsy (DRE) based on radiomic...

Developing a prediction model for cognitive impairment in older adults following critical illness.

BACKGROUND: New or worsening cognitive impairment or dementia is common in older adults following an...

Retinal imaging based glaucoma detection using modified pelican optimization based extreme learning machine.

Glaucoma is defined as progressive optic neuropathy that damages the structural appearance of the op...

Comparison analysis between standard polysomnographic data and in-ear-electroencephalography signals: a preliminary study.

STUDY OBJECTIVES: Polysomnography (PSG) currently serves as the benchmark for evaluating sleep disor...

Estimating global phase synchronization by quantifying multivariate mutual information and detecting network structure.

In neuroscience, phase synchronization (PS) is a crucial mechanism that facilitates information proc...

STANet: A Novel Spatio-Temporal Aggregation Network for Depression Classification with Small and Unbalanced FMRI Data.

: Early diagnosis of depression is crucial for effective treatment and suicide prevention. Tradition...

MACNet: A Multidimensional Attention-Based Convolutional Neural Network for Lower-Limb Motor Imagery Classification.

Decoding lower-limb motor imagery (MI) is highly important in brain-computer interfaces (BCIs) and r...

Enhancement and evaluation for deep learning-based classification of volumetric neuroimaging with 3D-to-2D knowledge distillation.

The application of deep learning techniques for the analysis of neuroimaging has been increasing rec...

Machine learning-based diagnostic model for stroke in non-neurological intensive care unit patients with acute neurological manifestations.

Stroke is a neurological complication that can occur in patients admitted to the intensive care unit...

MRI classification and discrimination of spinal schwannoma and meningioma based on deep learning.

BACKGROUD: Schwannoma (SCH) and meningiomas (MEN) are the two most common primary spinal cord tumors...

Segmentation of Low-Grade Brain Tumors Using Mutual Attention Multimodal MRI.

Early detection and precise characterization of brain tumors play a crucial role in improving patien...

Use of Artificial Intelligence in Imaging Dementia.

Alzheimer's disease is the most common cause of dementia in the elderly population (aged 65 years an...

Predicting executive functioning from walking features in Parkinson's disease using machine learning.

Parkinson's disease is characterized by motor and cognitive deficits. While previous work suggests a...

Current update on the neurological manifestations of long COVID: more questions than answers.

Since the outbreak of the COVID-19 pandemic, there has been a global surge in patients presenting wi...

BPEN: Brain Posterior Evidential Network for trustworthy brain imaging analysis.

The application of deep learning techniques to analyze brain functional magnetic resonance imaging (...

Telerehabilitation using a 2-D planar arm rehabilitation robot for hemiparetic stroke: a feasibility study of clinic-to-home exergaming therapy.

BACKGROUND: We evaluated the feasibility, safety, and efficacy of a 2D-planar robot for minimally su...

Effective Alzheimer's disease detection using enhanced Xception blending with snapshot ensemble.

Alzheimer's disease (AD), a prevalent neurodegenerative disorder, leads to progressive dementia, whi...

Improving care for amyotrophic lateral sclerosis with artificial intelligence and affective computing.

BACKGROUND: Patients with ALS often face difficulties expressing emotions due to impairments in faci...

Deep-learning assessment of hippocampal magnetic susceptibility in Alzheimer's disease.

BACKGROUND: Quantitative susceptibility mapping (QSM) is pivotal for analyzing neurodegenerative dis...

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