Neurology

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

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PADS-Net: GAN-based radiomics using multi-task network of denoising and segmentation for ultrasonic diagnosis of Parkinson disease.

Parkinson disease (PD) is a prevalent neurodegenerative disorder, and its accurate diagnosis is cruc...

Utilizing natural language processing to identify pediatric patients experiencing status epilepticus.

PURPOSE: Compare the identification of patients with established status epilepticus (ESE) and refrac...

Unveiling neural activity changes in mild cognitive impairment using microstate analysis and machine learning.

BACKGROUND: Mild cognitive impairment (MCI) is recognized as a condition that may increase the risk ...

Artificial intelligence empowered voice generation for amyotrophic lateral sclerosis patients.

Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease that can result in a progressive ...

Multimodal fuzzy logic-based gait evaluation system for assessing children with cerebral palsy.

Gait analysis is crucial for identifying functional deviations from the normal gait cycle and is ess...

Task relevant autoencoding enhances machine learning for human neuroscience.

In human neuroscience, machine learning can help reveal lower-dimensional neural representations rel...

VoxelMorph-Based Deep Learning Motion Correction for Ultrasound Localization Microscopy of Spinal Cord.

Accurate assessment of spinal cord vasculature is important for the urgent diagnosis of injury and s...

Harnessing the potential of human induced pluripotent stem cells, functional assays and machine learning for neurodevelopmental disorders.

Neurodevelopmental disorders (NDDs) affect 4.7% of the global population and are associated with del...

EEG microstate analysis and machine learning classification in patients with obsessive-compulsive disorder.

BACKGROUND: Microstate characterization of electroencephalogram (EEG) is a data-driven approach to e...

Deep learning-based differential gut flora for prediction of Parkinson's.

BACKGROUND: There had been extensive research on the role of the gut microbiota in human health and ...

Attention-Guided 3D CNN With Lesion Feature Selection for Early Alzheimer's Disease Prediction Using Longitudinal sMRI.

Predicting the progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) is criti...

Interpretable Multi-Branch Architecture for Spatiotemporal Neural Networks and Its Application in Seizure Prediction.

Currently, spatiotemporal convolutional neural networks (CNNs) for electroencephalogram (EEG) signal...

DCTP-Net: Dual-Branch CLIP-Enhance Textual Prompt-Aware Network for Acute Ischemic Stroke Lesion Segmentation From CT Image.

Detecting early ischemic lesions (EIL) in computed tomography (CT) images is crucial for reducing di...

Multiscale Spatial-Temporal Feature Fusion Neural Network for Motor Imagery Brain-Computer Interfaces.

Motor imagery, one of the main brain-computer interface (BCI) paradigms, has been extensively utiliz...

MFRC-Net: Multi-Scale Feature Residual Convolutional Neural Network for Motor Imagery Decoding.

Motor imagery (MI) decoding is the basis of external device control via electroencephalogram (EEG). ...

Harmonic Wavelet Neural Network for Discovering Neuropathological Propagation Patterns in Alzheimer's Disease.

Emerging researchindicates that the degenerative biomarkers associated with Alzheimer's disease (AD)...

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