Latest AI and machine learning research in neurology for healthcare professionals.
Body mass index (BMI), type 2 diabetes (T2D) and associated cardiometabolic features modify Alzheimer's disease (AD) risk, yet shared mechanisms remain poorly understood. Using sex- and age-stratified genotyping data for BMI and T2D, we investigate how these traits converge on shared genetic pathways to AD risk. Employing multi-trait, machine learning and single-cell transcriptomics, we identify s...
Aging is asynchronous across cells and organs, but whether plasma proteins can capture cell type-specific aging and predict disease and mortality remains unknown. We developed machine learning models to estimate the biological age of more than 40 distinct cell types spanning neuronal, immune, glial, endocrine, epithelial, and musculoskeletal origins using over 7,000 plasma proteins measured in 60,...
Brain Foundation Models (BFMs) are transforming neuroscience by enabling scalable and transferable learning from neural signals, advancing both clinic...
Digital subtraction angiography (DSA) plays a central role in the diagnosis and treatment of cerebrovascular disease, yet its invasive nature and high...
Portable, ultra-low-field (ULF) magnetic resonance imaging has the potential to expand access to neuroimaging but currently suffers from coarse spatia...
INTRODUCTION: Cognitively unimpaired (CU) adults show substantial variation in their risk of developing mild cognitive impairment (MCI), yet most subt...
Automated EEG monitoring requires clinician-level precision for seizure detection and reporting. Clinical EEG recordings exceed LLM context windows, r...
Cognitive load, the mental effort required during working memory, is central to neuroscience, psychology, and human-computer interaction. Accurate ass...
Early Alzheimer's disease often evades timely detection because typical diagnostics are based on symptomatic thinking rather than intrinsic neurodegen...
Isolated REM sleep behavior disorder (iRBD) is a key prodromal marker of Parkinson's disease (PD), and video-polysomnography (vPSG) remains the diagno...
Predicting time-to-event outcomes when event times are interval censored is challenging because the exact event time is unobserved. Many existing surv...
While cervical arthroplasty using Total Disc Replacement (TDR) implants is an established treatment for persistent neck and arm pain, revision rates l...
To be practical for real-life applications, models for brain-computer interfaces must be easily and quickly deployable on new subjects, effective on a...
The absence of pre-hospital physiological data in standard clinical datasets fundamentally constrains the early prediction of stroke, as patients typi...
Isolated REM sleep behavior disorder (iRBD) is a key prodromal marker of Parkinson's disease (PD), and video-polysomnography (vPSG) remains the diagno...
Background: Conventional evaluations of digital health interventions typically assess mean treatment effects, potentially masking heterogeneous impact...
Introduction: Plasma phosphorylated tau-217 is widely used as a plasma-based biomarker for Alzheimer's Disease detection, demonstrating superior accur...
-Synuclein (-syn) strains can serve as discriminators between Parkinson's disease (PD) and related -synucleinopathies. The relationship between -syn s...
Skull stripping magnetic resonance images (MRI) of the human brain is an important process in many image processing techniques, such as automatic segm...
We study homology of ample groupoids via the compactly supported Moore complex of the nerve. Let $A$ be a topological abelian group. For $n\ge 0$ set ...