Neurology

Accelerometry-Derived REM Sleep Behavior Disorder Predicts Future Parkinson's Disease in the UK Biobank

Estimating Parkinson's disease (PD) risk years before diagnosis remains an unmet need. We applied a validated machine learning classifier for REM sleep behavior disorder (RBD) detection to 7-day wrist accelerometry data in 87,975 UK Biobank participants followed for 10 years. Participants in the highest RBD risk stratum (>99th percentile) had an approximately fivefold increased hazard of incident ...

Hemispheric Asymmetry Features and Interpretable Machine Learning for Focal Cortical Dysplasia Classification in Drug-Resistant Epilepsy

Focal cortical dysplasia (FCD) is a principal cause of pharmacoresistant focal epilepsy, yet its structural MRI signature, subtle cortical thickening, blurring of the gray-white matter junction, is frequently undetected even by experienced neuroradiologists, delaying or precluding referral for curative surgical resection. Here we develop a machine learning pipeline for FCD detection that prioritiz...

Comparative Performance of Clinical Scoring Systems for Early Mortality Prediction in Blunt Traumatic Brain Injury

Background: Early risk stratification in traumatic brain injury (TBI) is essential for timely triage, resource allocation, and clinical decision-makin...

Automated Multisource Electronic Frailty Index in Acute Ischemic Stroke: Development and Clinical Utility

Background: Frailty is common in acute ischemic stroke (AIS) and predicts poor outcomes, but is not routinely captured in acute stroke care. Manual fr...

EEG-SpikeAgent: Agentic Closed-Loop Program Synthesis for Automated EEG Spike Detection

Automated detection of interictal epileptiform discharges in scalp electroencephalography (EEG) is clinically important, but recent high-performing de...

KinEMbed: Decoding Kinematics from Electromyography via Cross-Modal Contrastive Learning

Decoding hand kinematics from surface electromyography (EMG) is a core challenge in wearable biosignal processing with clinical relevance for prosthet...

UniSpine-GS: An Efficient Physics-Aware Gaussian Framework for Cross-Modality Multi-view Spine Image Synthesis

The diagnosis of spinal diseases is often assisted by 3D imaging techniques in clinical practice. However, precise 3D spinal assessment is limited by ...

Lightweight ML-Based Automatic Sleep Staging Framework with Constrained CNN and Mamba for Small-Sample EEG Datasets

Automatic sleep staging is a key technology for precise diagnosis and treatment of sleep disorders as well as long-term home sleep monitoring. Portabl...

A Multimodal Reasoning Typology for Grounding Chart-Image Coherence in Science Communication

Charts and images appear together throughout scientific publications, yet most computational work does not characterize their coherence. We argue that...

Wavelet Scattering Transform for Interpretable Schizophrenia Biomarker Discovery and Classification from Resting-State EEG

Schizophrenia is a debilitating neuropsychiatric disorder characterized by profound cortical network dysregulation, for which objective, clinically tr...

Age and Social Observation Effects on Theta Synchrony and Its Role in Adolescent Post-Error Control: A Computational Approach

Error monitoring allows for detecting mistakes and adapting behavior. Error monitoring is associated with increased theta (4-7 Hz) EEG activity record...

RD-OMICS: An Integrative Multi-Omics Data Inventory in Rare Diseases

Rare diseases (RD) impact over 30 million individuals in the United States, yet fewer than 5% of the identified conditions have FDA-approved treatment...

Unveiling Cerebrospinal Fluid Protein Biomarkers in Pediatric Acute Lymphoblastic Leukemia Using Proximity Extension Assay

Abstract Background: Acute Lymphoblastic Leukemia (ALL) is a highly heterogeneous pediatric malignancy. Despite high survival rates, relapse and the i...

EEG biomarkers of reinforcement learning and motivation: A multi-task battery

Serotonin and dopamine make dissociable contributions to reinforcement learning (RL) sub-components, yet we lack neural biomarkers capable of detectin...

Predicting Early Stages Of Alzheimer's Disease And Identifying Key Biomarkers Using Deep Artificial Neural Network And Ensemble Of Machine Learning Methodologies

Alzheimers disease (AD) is a brain disorder that develops slowly and mainly affects memory, thinking, language, and daily activities. It is one of the...

A 3D Brain Geometry Toolkit for Multisite Neuroimaging Analysis

Compared to traditional gross volumetrics, surface- based models provide greater spatial precision for understanding brain alterations related to deve...

NeuroBridge: Bridging Multi-Task MRI Knowledge for Neurodegenerative Disease Diagnosis

INTRODUCTION: Accurate MRI-based identification of Alzheimer's disease (AD), mild cognitive impairment (MCI), and related dementias remains challengin...

SubGaitNet: A Decision-Oriented and Interpretable AI Framework for Robust GRF-Based Gait Assessment in Neurological and Musculoskeletal Care

Ground reaction force (GRF)-based gait analysis provides objective, non-invasive evidence for neurological and musculoskeletal assessment, but its tra...

Attitudes of People Living with Dementia and their Carers towards the use of Generative Artificial Intelligence to inform Structured Medication Reviews

Background: Polypharmacy is common in people living with dementia (PLwD) and associated with adverse outcomes. Although Structured Medication Reviews ...

Machine learning on magnetoencephalography data yields generalizable low-dimensional neural fingerprints that distinguish individuals across task conditions

Individual brains are unique in structure and function. Functional differences are captured by neural fingerprints, which reflect individual differenc...