Latest AI and machine learning research in neurology for healthcare professionals.
People with Down syndrome have higher age-specific mortality rates compared to the general population as well as peers with other intellectual and developmental disabilities. While a large proportion of mortality is attributable to Alzheimers disease, many die prior to Alzheimers diagnosis and some live to old ages, dying without Alzheimers. Our objectives were to use 11 years of Medicaid and Medi...
Deep learning classifiers applied to structural MRI (sMRI) have achieved high performance in detecting Alzheimer's Disease (AD), yet systematic investigation of their failure modes remains limited. In this study, we trained two deep learning architectures to classify AD from cognitively normal (CN) participants using sMRI data from the ADNI dataset, and examined whether misclassifications persist ...
Background. Predicting conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) is central to trial enrichment and care planning, y...
Foundation models pretrained using self-supervised learning have transformed computer vision by learning transferable representations from large-scale...
Real-time EEG classification on edge devices is bottlenecked by the floating-point arithmetic of conventional neural networks. We investigated Differe...
A hallmark of neurodegenerative diseases such as Alzheimer's and Parkinson's is the aberrant aggregation of proteins into amyloid fibrils, and small m...
Deep brain stimulation (DBS) is effective for treatment-refractory obsessive-compulsive disorder (OCD), but outcomes are heterogeneous and non-respond...
Electroencephalography (EEG)-based emotion recognition captures affective neural signals with high temporal precision, but cross-subject variability a...
Focal cortical dysplasia (FCD) is one of the leading structural causes of drug-resistant focal epilepsy, yet its subtle and heterogeneous imaging char...
Robotic systems increasingly demand tactile sensing that approaches the adaptability and resolution of human skin to enable dexterous manipulation and...
Retinal layer segmentation in Optical Coherence Tomography (OCT) is a fundamental step for extracting quantitative biomarkers of retinal structure. In...
Background. Early diagnosis and intervention are crucial in multiple sclerosis (MS), yet diagnostic delays are common. Large language models (LLMs) su...
Background: Post-stroke dysphagia (PSD) contributes to aspiration, pneumonia, malnutrition, prolonged hospitalization and mortality. We evaluated the ...
White matter lesion (WML) identification, assessment, and characterization using magnetic resonance imaging (MRI) are fundamental for diagnosis and mo...
Sleep apnea diagnosis via polysomnography remains resource intensive and relies on time consuming manual data analysis and scoring. Recent work has de...
Copper (Cu) is an essential metal involved in neurobiological processes including energy metabolism and neurotransmission, yet dysregulated Cu levels ...
INTRODUCTION: Brain age gap (BAG) is the difference between a person's chronological age and the age predicted from the structural appearance of their...
Amyotrophic lateral sclerosis (ALS) is a progressive and heterogeneous neurodegenerative disease in which predicting clinically meaningful milestones,...
Seizure diagnosis from EEG signals is a critical yet persistently challenging task, due to the complicated neural dynamics and the spurious connection...
Background & Methods: The multifaceted physical nature of heritable cognitive impairment in dementia presents significant challenges for traditional l...