Neurology

Graph Convolutional Networks Enable Fast Hemorrhagic Stroke Monitoring With Electrical Impedance Tomography.

OBJECTIVE: To develop a fast image reconstruction method for stroke monitoring with electrical imped...

Convolutional neural network-derived neurofibrillary tangle classifiers: Investigative tools to identify maturation levels and explore post-translational modifications using laser capture microdissection coupled mass spectrometry.

Post-translational modifications (PTM) of tau are implicated in Alzheimer disease (AD) progression a...

Biases in an artificial intelligence image-generator's depictions of healthy aging and Alzheimer's.

OBJECTIVE: This content analysis study investigates potential biases in image generation by 2 artifi...

Prediction of anti-epileptic drug response of patients based on peripheral blood RNA profiles and machine learning.

OBJECTIVE: In this study, we aimed to develop a method for predicting the response of patients to th...

Functional and Clinical: An Explainable Deep Learning Model for Multimodal Alzheimer's Disease Classification.

PURPOSE: Functional magnetic resonance imaging (fMRI) and deep learning models can classify Alzheime...

Monitoring the lateral ventricles in the presence of intracranial hemorrhage using automated dual segmentation.

BACKGROUND: Segmentation of intracranial hemorrhage (ICH) alongside the brain's ventricles can provi...

Radiation-free Cobb angle estimation in adolescent scoliosis using surface topography and a linear regression model.

Scoliosis, the most common spinal deformity in adolescents, requires frequent radiographic follow-up...

SBTM: epileptic seizure prediction from EEG signal using deep learning in blockchain-enabled smart healthcare monitoring with IoT networking.

Functional and Structural Evidence of Neurofluid Circuit Aberrations in Huntington Disease.

OBJECTIVE: Disrupted neurofluid regulation may contribute to neurodegeneration in Huntington disease...

Investigation of Bias Using ChatGPT-4 in Pain Management and Patient Profiling.

BACKGROUND: Large language models, such as ChatGPT (cGPT), are being integrated increasingly into cl...

Constructing fine-grained subcortical atlases with connectional consensus graph representation learning.

Objective.The complex internal organization of subcortical structures forms the foundation of critic...

Smart assistive technologies for neurodisorders: A review on AI, IoT, and wearable systems for enhanced patient care.

Neurological disorders of the brain and spinal cord affect millions of individuals worldwide and con...

Distinct clinical clusters of paediatric patients with status epilepticus: Retrospective cohort study.

AIM: To characterize the clinical features, management, and outcomes of paediatric patients with sta...

Real-world evaluation of an automated EEG spike detection software in a tertiary centre compared to a clinical reference standard.

BACKGROUND: Interictal epileptiform discharges (IEDs) are transient spikes or waves that occur in el...

Data Augmentation for Subject-Independent SSVEP-BCIs via Simultaneous Spatial-Energy Representation.

OBJECTIVE: Data augmentation is important for enhancing subject-independent classification in deep l...

Clinical Validation of Deep Learning-Accelerated versus Wave-CAIPI Postcontrast 3D T1-MPRAGE for Evaluation of Intracranial Enhancing Lesions.

BACKGROUND AND PURPOSE: Deep learning (DL) reconstruction methods have shown promise in accelerating...

Health trajectories of patients with amyotrophic lateral sclerosis before and after initiation of non-invasive ventilation: a French nationwide database analysis.

BACKGROUND: Management of amyotrophic lateral sclerosis (ALS) is complicated by heterogeneous presen...

Alzheimer's disease diagnosis support for brain perfusion SPECT scans in a real-world clinical cohort.

BackgroundDementia diagnosis is challenging and often delayed. Brain imaging techniques such as sing...

Adversarial robust EEG-based brain-computer interfaces using a hierarchical convolutional neural network.

Brain-Computer Interfaces (BCIs) based on electroencephalography (EEG) are widely used in motor reha...

Balancing noise reduction and neural signature preservation in EEG biometrics.

EEG-based subject identification is an emerging biometric approach with strong potential for secure ...

The role of dentists in the recognition of neurodegenerative and systemic conditions with neurological involvement.

Dentists are often the first healthcare providers to observe subtle orofacial and behavioral changes...