Neurology

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

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Parkinson's disease detection and classification using EEG based on deep CNN-LSTM model.

The progressive loss of motor function in the brain is a hallmark of Parkinson's disease (PD). Elect...

Deep learning classification of reading disability with regional brain volume features.

Developmental reading disability is a prevalent and often enduring problem with varied mechanisms th...

Stereology neuron counts correlate with deep learning estimates in the human hippocampal subregions.

Hippocampal subregions differ in specialization and vulnerability to cell death. Neuron death and hi...

Self-Supervised EEG Emotion Recognition Models Based on CNN.

Emotion plays crucial roles in human life. Recently, emotion classification from electroencephalogra...

Learning Curve of Robot-Assisted Lymph Node Dissection of the Left Recurrent Laryngeal Nerve: A Retrospective Study of 417 Patients.

OBJECTIVE: Left recurrent laryngeal nerve (no.106recL) lymph node dissection is a challenging proced...

A unique color-coded visualization system with multimodal information fusion and deep learning in a longitudinal study of Alzheimer's disease.

PURPOSE: Automated diagnosis and prognosis of Alzheimer's Disease remain a challenging problem that ...

Deep learning prediction of motor performance in stroke individuals using neuroimaging data.

The degree of motor impairment and profile of recovery after stroke are difficult to predict for eac...

The Impact of Fatty Infiltration on MRI Segmentation of Lower Limb Muscles in Neuromuscular Diseases: A Comparative Study of Deep Learning Approaches.

BACKGROUND: Deep learning methods have been shown to be useful for segmentation of lower limb muscle...

All answers are in the images: A review of deep learning for cerebrovascular segmentation.

Cerebrovascular imaging is a common examination. Its accurate cerebrovascular segmentation become an...

NeuronMotif: Deciphering cis-regulatory codes by layer-wise demixing of deep neural networks.

Discovering DNA regulatory sequence motifs and their relative positions is vital to understanding th...

Explainable prediction of daily hospitalizations for cerebrovascular disease using stacked ensemble learning.

BACKGROUND: With the prevalence of cerebrovascular disease (CD) and the increasing strain on healthc...

Interpretable machine learning approach for neuron-centric analysis of human cortical cytoarchitecture.

The complexity of the cerebral cortex underlies its function and distinguishes us as humans. Here, w...

A neurocognitive view on the depiction of social robots.

While we applaud the careful breakdown by Clark and Fischer of the representation of social robots h...

LightSeizureNet: A Lightweight Deep Learning Model for Real-Time Epileptic Seizure Detection.

The monitoring of epilepsy patients in non-hospital environment is highly desirable, where ultra-low...

Fully Complex-Valued Dendritic Neuron Model.

A single dendritic neuron model (DNM) that owns the nonlinear information processing ability of dend...

Comparing representations and computations in single neurons versus neural networks.

Single-neuron-level explanations have been the gold standard in neuroscience for decades. Recently, ...

Artificial Intelligence for Neuroimaging and Musculoskeletal Radiology: Overview of Current Commercial Algorithms.

There is a rapidly increasing number of artificial intelligence (AI) products cleared by the Food an...

Decoding study-independent mind-wandering from EEG using convolutional neural networks.

. Mind-wandering is a mental phenomenon where the internal thought process disengages from the exter...

Comparison of Machine Learning Models for Brain Age Prediction Using Six Imaging Modalities on Middle-Aged and Older Adults.

Machine learning (ML) has transformed neuroimaging research by enabling accurate predictions and fea...

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