Neurology

Integrating metacognitive mechanisms optimizes EEG generative models via hierarchical regularization.

Obtaining sufficient electroencephalography (EEG) signals for training deep neural networks (DNNs) i...

DeepCRI: Real-time EEG-based Prognostication after Cardiac Arrest.

Accurate prediction of neurological outcome after cardiac arrest is essential for guiding intensive ...

Incorporating normal periventricular changes for enhanced pathological white matter hyperintensity segmentation: on multiclass deep learning approaches.

White matter hyperintensities (WMH) detected on FLAIR MRI sequences serve as important biomarkers fo...

Association of initial core volume on non-contrast CT using a deep learning algorithm with clinical outcomes in acute ischemic stroke: a potential tool for selection and prognosis?

BACKGROUND: In an extended time window, contrast-based neuroimaging is valuable for treatment select...

The Insomnia EEG Score: a new tool for the classification of people with poor sleep.

Quantitative features could help objectively identify and grade insomnia severity, though there is c...

Multimodal cardiovascular risk profiling using self-supervised learning of polysomnography.

STUDY OBJECTIVES: Polysomnography (PSG) provides a comprehensive assessment of brain, cardiac, and r...

Statistically valid explainable black-box machine learning: applications in sex classification across species using brain imaging.

Sex classification using neuroimaging data has the potential to revolutionize personalized diagnosti...

Differential diagnosis of migraine and tension-type headache based on brain volumes using machine learning methods.

PURPOSE: Structural brain changes in migraine and tension-type headache (TTH) have mostly been inves...

Enhanced cortical connectivity during passive robotic-assisted gait training in individuals with spinal cord injury: An EEG study.

BACKGROUND: Robotic-assisted gait training (RAGT) has emerged as a promising strategy to promote neu...

Lower pre-treatment TMS-evoked cortical reactivity and alpha-band oscillatory dynamics predict efficacy of primary motor cortex neuromodulation for chronic pain.

Repetitive transcranial magnetic stimulation (rTMS) to the primary motor cortex (M1) provides signif...

Drawn-on-skin electronic tattoo as a closed-loop sensing-stimulation system for the muscles.

Simultaneous electromyography (EMG) sensing and closed-loop electrical stimulation (ES) could enable...

Neural Reconstruction in Disorders of Consciousness: Prospects and Emerging Challenges.

Reconstructing mental experience from brain activity is becoming increasingly feasible through advan...

Multimodal Machine Learning for Diabetic Peripheral Neuropathy Diagnosis: Methodological Advances and Future Directions.

MRI-Guided High-Intensity Focused Ultrasound in Movement Disorders: Targeting Pathologic Brain Circuits With Precision Imaging, From the AJR Special Series on Critical Anatomy.

MRI-guided high-intensity focused ultrasound (MRgHIFU) has emerged as an alternative to other neurom...

Interpretable deep learning reveals spatiotemporal MRI features of brain aging that align with neurodegeneration.

Cortical thinning and atrophy are hallmarks of brain aging that have been characterized using magnet...

Bidirectional Mamba-2 Boosts EEG Super-Resolution via Regression and Diffusion.

MOTIVATIONS: Electroencephalography (EEG) is a non-invasive method that records brain electrical act...

MAISNet: A Multi-Species Integrated Graph Neural Network for Acetylcholinesterase Inhibitor Screening.

MOTIVATION: Global population aging has led to a rapid increase in neurodegenerative disorders such ...

A novel machine learning approach for prediction of postoperative delirium using multi-domain features of high-density EEG.

Postoperative delirium (POD) poses a significant risk to patients, and accurate prediction of p...

Predicting post-stroke functional outcome using explainable machine learning and integrated data.

Functional outcome after acute ischemic stroke (AIS) varies widely, and existing prognostic scores m...

Feature selection leads to divergent neurobiological interpretations of brain-based machine learning biomarkers.

A central objective in human neuroimaging is to understand the neurobiology underlying cognition and...

Malignant Cerebral Edema after Large-Core Anterior Circulation Stroke in the Thrombectomy Era: Prediction and Neurocritical Care Pathways.

Large-core anterior circulation ischemic stroke (LCIS) complicated by malignant cerebral edema (MCE)...