Neurology

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

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Social anxiety prediction based on ERP features: A deep learning approach.

BACKGROUND: Social Anxiety Disorder is traditionally diagnosed using subjective scales that may lack...

Cross-subject emotion recognition in brain-computer interface based on frequency band attention graph convolutional adversarial neural networks.

BACKGROUND: Emotion is an important area in neuroscience. Cross-subject emotion recognition based on...

Advancing Tau PET Quantification in Alzheimer Disease with Machine Learning: Introducing THETA, a Novel Tau Summary Measure.

Alzheimer disease (AD) exhibits spatially heterogeneous 3- or 4-repeat tau deposition across partici...

Cost-Sensitive Weighted Contrastive Learning Based on Graph Convolutional Networks for Imbalanced Alzheimer's Disease Staging.

Identifying the progression stages of Alzheimer's disease (AD) can be considered as an imbalanced mu...

Brain Emotion Perception Inspired EEG Emotion Recognition With Deep Reinforcement Learning.

Inspired by the well-known Papez circuit theory and neuroscience knowledge of reinforcement learning...

SSGCNet: A Sparse Spectra Graph Convolutional Network for Epileptic EEG Signal Classification.

In this article, we propose a sparse spectra graph convolutional network (SSGCNet) for epileptic ele...

Memristive Circuit Implementation of Caenorhabditis Elegans Mechanism for Neuromorphic Computing.

To overcome the energy efficiency bottleneck of the von Neumann architecture and scaling limit of si...

A retrospective evaluation of the potential of ChatGPT in the accurate diagnosis of acute stroke.

PURPOSE: Stroke is a neurological emergency requiring rapid, accurate diagnosis to prevent severe co...

Super-Resolving and Denoising 4D flow MRI of Neurofluids Using Physics-Guided Neural Networks.

PURPOSE: To obtain high-resolution velocity fields of cerebrospinal fluid (CSF) and cerebral blood f...

SCINet: A Segmentation and Classification Interaction CNN Method for Arteriosclerotic Retinopathy Grading.

As a common disease, cardiovascular and cerebrovascular diseases pose a great harm threat to human w...

Auxiliary diagnostic method of Parkinson's disease based on eye movement analysis in a virtual reality environment.

Eye movement dysfunction is one of the non-motor symptoms of Parkinson's disease (PD). An accurate a...

Impact of acquisition area on deep-learning-based glaucoma detection in different plexuses in OCTA.

Glaucoma is a group of neurodegenerative diseases that can lead to irreversible blindness. Yet, the ...

Development of machine learning-based models for predicting risk factors in acute cerebral infarction patients: a clinical retrospective study.

OBJECTIVES: The aim of this study was to develop machine learning-based models for predicting acute ...

Can deep learning classify cerebral ultrasound images for the detection of brain injury in very preterm infants?

OBJECTIVES: Cerebral ultrasound (CUS) is the main imaging screening tool in preterm infants. The aim...

Deep learning for efficient reconstruction of highly accelerated 3D FLAIR MRI in neurological deficits.

OBJECTIVE: To compare compressed sensing (CS) and the Cascades of Independently Recurrent Inference ...

Construction and verification of a machine learning-based prediction model of deep vein thrombosis formation after spinal surgery.

BACKGROUND: Deep vein thromboembolism (DVT) is a common postoperative complication with high morbidi...

The Future of Sustainable Neurosurgery: Is a Moonshot Plan for Artificial Intelligence and Robot-Assisted Surgery Possible in Japan?

Japanese neurosurgery faces challenges such as a declining number of neurosurgeons and their concent...

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