Neurology

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

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Personalised screening tool for early detection of sarcopenia in stroke patients: a machine learning-based comparative study.

BACKGROUND: Sarcopenia is a common complication in patients with stroke, adversely affecting recover...

Coal and gas outburst prediction based on data augmentation and neuroevolution.

Coal and gas outburst (CGO) is a complicated natural disaster in underground coal mine production. I...

CT-Based Machine Learning Radiomics Analysis to Diagnose Dysthyroid Optic Neuropathy.

PURPOSE: To develop CT-based machine learning radiomics models used for the diagnosis of dysthyroid ...

Parkinson's disease tremor prediction towards real-time suppression: A self-attention deep temporal convolutional network approach.

Accurate prediction of Parkinson's disease tremor (PDT) is crucial for developing assistive technolo...

Towards realistic simulation of disease progression in the visual cortex with CNNs.

Convolutional neural networks (CNNs) and mammalian visual systems share architectural and informatio...

Geometric neural network based on phase space for BCI-EEG decoding.

The integration of Deep Learning (DL) algorithms on brain signal analysis is still in its nascent st...

Optimal design of a wheelchair-mounted robotic arm for activities of daily living.

PURPOSE: The increasing prevalence of upper limb dysfunctions due to stroke, spinal cord injuries, a...

A novel deep learning model combining 3DCNN-CapsNet and hierarchical attention mechanism for EEG emotion recognition.

Emotion recognition plays a key role in the field of human-computer interaction. Classifying and pre...

Machine learning classification of active viewing of pain and non-pain images using EEG does not exceed chance in external validation samples.

Previous research has demonstrated that machine learning (ML) could not effectively decode passive o...

Clinical efficacy of NIBS in enhancing neuroplasticity for stroke recovery.

BACKGROUND: For stroke patients, a therapeutic approach named Non-invasive brain stimulation (NIBS) ...

Interpretation of basal nuclei in brain dopamine transporter scans using a deep convolutional neural network.

OBJECTIVE: Functional imaging using the dopamine transporter (DAT) as a biomarker has proven effecti...

Explaining electroencephalogram channel and subband sensitivity for alcoholism detection.

Alcoholism, a progressive loss of control over alcohol consumption, deteriorates mental and physical...

A systematic literature review of machine learning techniques for the detection of attention-deficit/hyperactivity disorder using MRI and/or EEG data.

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental condition common in teenager...

Diabetic peripheral neuropathy detection of type 2 diabetes using machine learning from TCM features: a cross-sectional study.

AIMS: Diabetic peripheral neuropathy (DPN) is the most common complication of diabetes mellitus. Ear...

Sway frequencies may predict postural instability in Parkinson's disease: a novel convolutional neural network approach.

BACKGROUND: Postural instability greatly reduces quality of life in people with Parkinson's disease ...

Deep learning-based classification of diffusion-weighted imaging-fluid-attenuated inversion recovery mismatch.

The presence of a diffusion-weighted imaging (DWI)-fluid-attenuated inversion recovery (FLAIR) misma...

Application of Artificial Intelligence in Acute Ischemic Stroke: A Scoping Review.

Artificial intelligence (AI) is revolutionizing stroke care by enhancing diagnosis, treatment, and o...

Bridging Neuroscience and Machine Learning: A Gender-Based Electroencephalogram Framework for Guilt Emotion Identification.

This study explores the link between the emotion "guilt" and human EEG data, and investigates the in...

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