Latest AI and machine learning research in neurology for healthcare professionals.
Dementia encompasses diverse clinical syndromes where diseases of the brain can manifest as impaired cognitive abilities, such as in Alzheimer’s disease (AD) and behavioral-variant frontotemporal dementia (bvFTD). The diversity of symptom presentations often results in challenges in diagnosis. Crucial clinical information remains in unstructured narrative notes within electronic health records (EH...
This study introduces an innovative sex-stratified methodology for the identification of Parkinson’s disease (PD) using vertical ground reaction force (VGRF) data obtained from foot sensors during ambulation. We devised and evaluated four distinct recurrent neural network designs. We identified a substantial deficiency in existing diagnostic methodologies that infrequently utilize sex-stratified t...
Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by heterogeneous pathophysiological changes that begin years before symptoms em...
Neonatal seizures cause significant morbidity and mortality, both acutely and in the long term, contributing to adverse neurodevelopmental outcomes. T...
The reliability of MRI-derived measures critically depends on image quality. Poor-quality scans can obscure anatomical detail and compromise the accur...
With dementia diagnoses in the UK projected to exceed one million in 2025, there is an urgent need for scalable and effective care solutions to ease p...
In active vision, the brain receives and encodes discontinuous streams of visual information gated by saccadic eye movements. Saccadic modulation of n...
Sleep interventions targeting slow-wave activity (SWA) show heterogeneous effects across individuals. We investigated whether pre-sleep brain states p...
Dementia poses an escalating global health burden, yet its underlying mechanisms remain incompletely understood. In this large-scale, targeted metabol...
Eye movements are key biomarkers for diagnosing and monitoring neuro-otological, neuro-ophthalmological and neurodegenerative disorders. Video-oculogr...
To leverage sleep foundation models trained on large datasets of polysomnography for neurological disorder detection during an awake state. Three publ...
To improve the detection performance of epileptic electroencephalogram (EEG) signals and address their non-stationary characteristics, this paper comp...
Accurate early prediction of neurological outcomes in comatose patients after cardiac arrest is critical for guiding therapeutic decisions and improvi...
Timely intensive rehabilitation is crucial to contrast the negative escalation of events that follow a stroke injury, to promote tissue regeneration, ...
Arachnoiditis, a painful and potentially disabling neurological condition, results from persistent inflammation of the spinal cord pia-arachnoid membr...
Sleep disorders pose a major global health burden and are associated with a wide range of adverse health outcomes. Polysomnography (PSG) is the gold s...
Magnetic resonance imaging (MRI) plays a central role in diagnosing multiple sclerosis (MS), yet conventional T2-FLAIR imaging provides limited specif...
Delayed Dark-Adapted vision Recovery (DAR) is a known biomarker for Age-related Macular Degeneration (AMD); however, its measurement is often cumberso...
We investigated whether sleep features from multi-night, at-home in-ear EEG could distinguish mild cognitive impairment (MCI) from cognitively normal ...
Mild traumatic brain injury (mTBI) is a heterogeneous condition with long-term sequelae, yet diagnosis in the chronic stage remains limited by relianc...