Neurology

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

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Event-based optical flow on neuromorphic processor: ANN vs. SNN comparison based on activation sparsification.

Spiking neural networks (SNNs) for event-based optical flow are claimed to be computationally more e...

A novel intelligent grade classification architecture for Patent Foramen Ovale by Contrast Transthoracic Echocardiography based on deep learning.

Patent foramen ovale (PFO) is one of the main causes of ischemic stroke. Due to the complex characte...

Subtractive genomics approach: A guide to unveiling therapeutic targets across pathogens.

Subtractive genomics is an adaptable bioinformatics technique that is used to identify potential the...

The Cognivue Amyloid Risk Measure (CARM): A Novel Method to Predict the Presence of Amyloid with Cognivue Clarity.

INTRODUCTION: At the present time, clinical detection of individuals who have amyloid in their brain...

Single-Component Double-Emissive Ratiometric Probe: Toward Machine Learning Driven Detection and Discrimination of Neurological Biomarkers.

This study presents an attractive single-component ratiometric fluorescent sensor that utilizes the ...

Prediction of new-onset migraine using clinical-genotypic data from the HUNT Study: a machine learning analysis.

BACKGROUND: Migraine is associated with a range of symptoms and comorbid disorders and has a strong ...

DP-MP: a novel cross-subject fatigue detection framework with DANN-based prototypical representation and mix-up pairwise learning.

. Electroencephalography (EEG) is widely recognized as an effective method for detecting fatigue. Ho...

Ensemble deep learning for Alzheimer's disease diagnosis using MRI: Integrating features from VGG16, MobileNet, and InceptionResNetV2 models.

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by the accumulation of amyloi...

Interim results of exoskeletal wearable robot for gait recovery in subacute stroke patients.

Exoskeletons have been proposed for potential clinical use to improve ambulatory function in patient...

Explainable artificial intelligence to diagnose early Parkinson's disease via voice analysis.

Parkinson's disease (PD) is a neurodegenerative disorder affecting motor control, leading to symptom...

EMG features dataset for arm activity recognition.

This study presents a dataset on hand gesture recognition using electromyography (EMG) signals. The ...

The impact of Alzheimer's disease on cortical complexity and its underlying biological mechanisms.

BACKGROUND: Alzheimer's disease (AD) might impact the complexity of cerebral cortex, and the underly...

Artificial neural networks applied to somatosensory evoked potentials for migraine classification.

BACKGROUND: Finding a biomarker to diagnose migraine remains a significant challenge in the headache...

An effective PO-RSNN and FZCIS based diabetes prediction and stroke analysis in the metaverse environment.

Chronic disease (CD) like diabetes and stroke impacts global healthcare extensively, and continuous ...

A quantum inspired machine learning approach for multimodal Parkinson's disease screening.

Parkinson's disease, currently the fastest-growing neurodegenerative disorder globally, has seen a 5...

A muscle synergy-based method to improve robot-assisted movements.

There is increasing interest in using assistive robotic devices to support motor re-learning and rec...

A fine-tuned convolutional neural network model for accurate Alzheimer's disease classification.

Alzheimer's disease (AD) is one of the primary causes of dementia in the older population, affecting...

Unsupervised Domain Adaptation for Cross-Modality Cerebrovascular Segmentation.

Cerebrovascular segmentation from time-of-flight magnetic resonance angiography (TOF-MRA) and comput...

DEMENTIA: A Hybrid Attention-Based Multimodal and Multi-Task Learning Framework With Expert Knowledge for Alzheimer's Disease Assessment From Speech.

The prevalence of Alzheimer's disease (AD) is rising annually, imposing a severe burden on patients ...

A Hybrid Artificial Intelligence System for Automated EEG Background Analysis and Report Generation.

Electroencephalography (EEG) plays a crucial role in the diagnosis of various neurological disorders...

LGG-NeXt: A Next Generation CNN and Transformer Hybrid Model for the Diagnosis of Alzheimer's Disease Using 2D Structural MRI.

Incurable Alzheimer's disease (AD) plagues many elderly people and families. It is important to accu...

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