Neurology

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

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Machine learning of time series data using persistent homology.

This study proposes a novel method for time-series analysis based on persistent homology. Traditiona...

EmoTrans attention based emotion recognition using EEG signals and facial analysis with expert validation.

Emotion recognition via EEG signals and facial analysis becomes one of the key aspects of human-comp...

Improving EEG based brain computer interface emotion detection with EKO ALSTM model.

Decoding signals from the CNS brain activity is done by a computer-based communication device called...

Proteomic risk scores for predicting common diseases using linear and neural network models in the UK biobank.

Plasma proteomics provides a unique opportunity to enhance disease prediction by capturing protein e...

Automatic melanoma detection using an optimized five-stream convolutional neural network.

Melanoma is among the deadliest forms of malignant skin cancer, with the number of cases increasing ...

DDoS attack detection in intelligent transport systems using adaptive neuro-fuzzy inference system.

An intelligent transportation system consists of a variety of applications that analyze and exchange...

Enhanced schizophrenia detection using multichannel EEG and CAOA-RST-based feature selection.

Schizophrenia is a mental disorder characterized by hallucinations, delusions, disorganized thinking...

Towards decoding motor imagery from EEG signal using optimized back propagation neural network with honey badger algorithm.

The importance of using Brain-Computer Interface (BCI) systems based on electro encephalography (EEG...

A modified generative adversarial networks method for assisting the diagnosis of deep venous thrombosis complications in stroke patients.

Discriminate deep vein thrombosis, one of the complications in early stroke patients, in order to as...

Schizophrenia detection from electroencephalogram signals using image encoding and wrapper-based deep feature selection approach.

Schizophrenia is a persistent and serious mental illness that leads to distortions in cognition, per...

STIED: a deep learning model for the spatiotemporal detection of focal interictal epileptiform discharges with MEG.

Magnetoencephalography (MEG) allows the non-invasive detection of interictal epileptiform discharges...

Design of a deep fusion model for early Parkinson's disease prediction using handwritten image analysis.

Parkinson's Disease (PD) is a deteriorating condition that mostly affects older people. The lack of ...

FSID: a novel approach to human activity recognition using few-shot weight imprinting.

Accurate recognition of human activities from gait sensory data plays a vital role in healthcare and...

Machine learning model for predicting Amyloid-β positivity and cognitive status using early-phase F-Florbetaben PET and clinical features.

This study developed machine learning models to predict Aβ positivity in Alzheimer's disease by inte...

Integrative machine learning and molecular simulation approaches identify GSK3β inhibitors for neurodegenerative disease therapy.

Neurodegenerative diseases (NDDs), including Alzheimer's disease (AD) and Parkinson's disease (PD), ...

Brainstem noradrenergic modulation of the kisspeptin neuron GnRH pulse generator in mice.

Brainstem noradrenaline (NA) neurons modulate the activity of many neural networks including those r...

A simplified minimodel of visual cortical neurons.

Artificial neural networks (ANNs) have been shown to predict neural responses in primary visual cort...

Experimental demonstration of third-order memristor-based artificial sensory nervous system for neuro-inspired robotics.

The sensory nervous system in animals enables the perception of external stimuli. Developing an arti...

Ultradeep N-glycoproteome atlas of mouse reveals spatiotemporal signatures of brain aging and neurodegenerative diseases.

The current depth of site-specific N-glycoproteomics is insufficient to fully characterize glycosyla...

Brain-wide input-output analysis of tuberal nucleus somatostatin neurons reveals hierarchical circuits for orchestrating feeding behavior.

Feeding is an innate behavior critical for survival but is also influenced by many non-nutritional f...

Developments in MRI radiomics research for vascular cognitive impairment.

Vascular cognitive impairment (VCI) is an umbrella term for diseases associated with cognitive decli...

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