Neurology

Artificial intelligence and telemedicine in epilepsy and EEG: A narrative review.

The emergence of telemedicine and artificial intelligence (AI) has set the stage for a possible revo...

PSSM-Sumo: deep learning based intelligent model for prediction of sumoylation sites using discriminative features.

Post-translational modifications (PTMs) are fundamental to essential biological processes, exerting ...

CTNet: a convolutional transformer network for EEG-based motor imagery classification.

Brain-computer interface (BCI) technology bridges the direct communication between the brain and mac...

Uncovering early predictors of cerebral palsy through the application of machine learning: a case-control study.

OBJECTIVE: Cerebral palsy (CP) is a group of neurological disorders with profound implications for c...

An extensible and unifying approach to retrospective clinical data modeling: the BrainTeaser Ontology.

Automatic disease progression prediction models require large amounts of training data, which are se...

Federated Learning in Glaucoma: A Comprehensive Review and Future Perspectives.

CLINICAL RELEVANCE: Glaucoma is a complex eye condition with varied morphological and clinical prese...

Deep learning to predict risk of lateral skull base cerebrospinal fluid leak or encephalocele.

PURPOSE: Skull base features, including increased foramen ovale (FO) cross-sectional area, are assoc...

CNVDeep: deep association of copy number variants with neurocognitive disorders.

BACKGROUND: Copy number variants (CNVs) have become increasingly instrumental in understanding the e...

Neuroethics and AI ethics: a proposal for collaboration.

The scientific relationship between neuroscience and artificial intelligence is generally acknowledg...

Unveiling the potential of machine learning approaches in predicting the emergence of stroke at its onset: a predicting framework.

A stroke is a dangerous, life-threatening disease that mostly affects people over 65, but an unhealt...

Assessment of inter-rater and intra-rater reliability of the Luna EMG robot as a tool for assessing upper limb proprioception in patients with stroke-a prospective observational study.

BACKGROUND: The aim of the study was to assess the inter-rater and intra-rater agreement of measurem...

Improving classification performance of motor imagery BCI through EEG data augmentation with conditional generative adversarial networks.

In brain-computer interface (BCI), building accurate electroencephalogram (EEG) classifiers for spec...

Myo-regressor Deep Informed Neural NetwOrk (Myo-DINO) for fast MR parameters mapping in neuromuscular disorders.

Magnetic Resonance (MR) parameters mapping in muscle Magnetic Resonance Imaging (mMRI) is predominan...

Schizophrenia diagnosis using the GRU-layer's alpha-EEG rhythm's dependability.

Verifying schizophrenia (SZ) can be assisted by deep learning techniques and patterns in brain activ...

Bio-inspired EEG signal computing using machine learning and fuzzy theory for decision making in future-oriented brain-controlled vehicles.

One kind of autonomous vehicle that can take instructions from the driver by reading their electroen...

Electrocardiogram-Based Artificial Intelligence to Discriminate Cardioembolic Stroke and Stratify Risk of Atrial Fibrillation After Stroke.

Development of predictive model for the neurological deterioration among mild traumatic brain injury patients using machine learning algorithms.

BACKGROUND: Mild traumatic brain injury (mTBI) comprises a majority of traumatic brain injury (TBI) ...

Learnable Brain Connectivity Structures for Identifying Neurological Disorders.

Brain networks/graphs have been widely recognized as powerful and efficient tools for identifying ne...

Harnessing Deep Learning Methods for Voltage-Gated Ion Channel Drug Discovery.

Voltage-gated ion channels (VGICs) are pivotal in regulating electrical activity in excitable cells ...

NeuroQuantify - An image analysis software for detection and quantification of neuron cells and neurite lengths using deep learning.

BACKGROUND: The segmentation of cells and neurites in microscopy images of neuronal networks provide...

Classification of optic neuritis in neuromyelitis optica spectrum disorders (NMOSD) on MRI using CNN with transfer learning and manipulation of pre-processing on augmentation.

Neuromyelitis optica spectrum disorder (NMOSD), also known as Devic disease, is an autoimmune centra...