Neurology

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

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Longitudinal structural MRI-based deep learning and radiomics features for predicting Alzheimer's disease progression.

BACKGROUND: Alzheimer's disease (AD) is the principal cause of dementia and requires the early diagn...

Remote clinical decision support tool for Parkinson's disease assessment using a novel approach that combines AI and clinical knowledge.

BACKGROUND: Early diagnosis of Parkinson's disease (PD) can assist in designing efficient treatments...

Machine learning predicts distinct biotypes of amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease that is universally fatal and has...

Computational mechanisms of neuroimaging biomarkers uncovered by multicenter resting-state fMRI connectivity variation profile.

Resting-state functional connectivity (rsFC) is increasingly used to develop biomarkers for psychiat...

Strengthening Africa's brain health and economic resilience.

Africa stands at a decisive moment in which urgent action is essential to safeguard its brain health...

Current Landscape and Future Directions Regarding Generative Large Language Models in Stroke Care: Scoping Review.

BACKGROUND: Stroke has a major impact on global health, causing long-term disability and straining h...

Clinical Application of Machine Learning in Biomedical Engineering for the Early Detection of Neurological Disorders.

Machine learning is increasingly recognized as a transformative tool in the diagnosis and prognosis ...

Alzheimer's disease risk prediction using machine learning for survival analysis with a comorbidity-based approach.

Alzheimer's disease (AD) presents a pressing global health challenge, demanding improved strategies ...

Contrastive representation learning with transformers for robust auditory EEG decoding.

Decoding of continuous speech from electroencephalography (EEG) presents a promising avenue for unde...

Statistical variability in comparing accuracy of neuroimaging based classification models via cross validation.

Machine learning (ML) has significantly transformed biomedical research, leading to a growing intere...

MyoPose: position-limb-robust neuromechanical features for enhanced hand gesture recognition in colocated sEMG-pFMG armbands.

Surface electromyography (sEMG) and pressure-based force myography (pFMG) are two complementary moda...

Multivideo Models for Classifying Hand Impairment After Stroke Using Egocentric Video.

OBJECTIVES: After stroke, hand function assessments are used as outcome measures to evaluate new reh...

Transformer-Based Deep Learning Approaches for Speech-Based Dementia Detection: A Systematic Review.

As the population of older adults continues growing, so will the need for cost-effective approaches ...

Evaluating crowdsourcing for ICU EEG annotation: A comparison with expert performance.

OBJECTIVE: Detection of seizures and rhythmic or periodic patterns (SRPPs) on electroencephalography...

Stakeholder Perspectives on Trustworthy AI for Parkinson Disease Management Using a Cocreation Approach: Qualitative Exploratory Study.

BACKGROUND: Parkinson disease (PD) is the fastest-growing neurodegenerative disorder in the world, w...

Targeting neurodegeneration: three machine learning methods for G9a inhibitors discovery using PubChem and scikit-learn.

In light of the increasing interest in G9a's role in neuroscience, three machine learning (ML) model...

Neural Synchrony and Consumer Behavior: Predicting Friends' Behavior in Real-World Social Networks.

The endogenous aspect of social influence, reflected in the spontaneous alignment of behaviors withi...

Strategies to Decipher Neuron Identity from Extracellular Recordings in Behaving Nonhuman Primates.

Identification of the neuron type is critical when using extracellular recordings in awake, behaving...

PyNoetic: A modular python framework for no-code development of EEG brain-computer interfaces.

Electroencephalography (EEG)-based Brain-Computer Interfaces (BCIs) have emerged as a transformative...

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