Latest AI and machine learning research in neurology for healthcare professionals.
White matter hyperintensities (WMH) and ischaemic stroke lesions (ISL) are imaging features associated with cerebral small vessel disease (SVD) that are visible on brain magnetic resonance imaging (MRI) scans. The development and validation of deep learning models to segment and differentiate these features is difficult because they visually confound each other in the fluid-attenuated inversion re...
Chronic pain involves natural intensity fluctuations that patients cannot control, contributing to learned helplessness and functional impairment. Detecting spontaneous pain decreases could enable precisely timed interventions that enhance perceived control. However, existing research on objective pain assessment has focused primarily on estimating static intensity from short, predictable stimuli ...
One-third of the world's 70 million people with epilepsy have seizures that are not controlled by medication; and implantable devices are an exciting ...
The ventral tegmental area is the primary source of dopaminergic input to the human prefrontal cortex and plays a central role in reinforcement learni...
Synthetic neuroimaging data can mitigate critical limitations of real-world datasets, including the scarcity of rare phenotypes, domain shifts across ...
Comprehending how forces are applied to an object during manipulation can help provide important insights into the quality of behavior in daily tasks....
Background: Early diagnosis of dementia can significantly improve care planning and patient outcomes while delaying progression. Machine learning algo...
Multivariate analyses of M/EEG data are typically performed on neural responses time-locked to discrete stimulus onsets. Such designs usually reveal h...
Accurate identification of non-enhancing hypercellular (NEH) tumor regions is an unmet need in neuro-oncological imaging, with significant implication...
Electroencephalogram (EEG) decoding is a critical component of medical diagnostics, rehabilitation engineering, and brain-computer interfaces. However...
Objective Accurate and scalable disease phenotyping from electronic health records (EHRs) is foundational for predictive modeling and precision medici...
Background: Automated thrombus segmentation on CT imaging could enable routine extraction of clot volume and other biomarkers in large vessel occlusio...
Electric field (EF) stimulation is an emerging neuromodulatory strategy for promoting the repair and functional recovery of degenerated neural network...
Individuals with post-stroke aphasia live with long-term disabilities, yet they do not know whether they will improve their communication and cognitiv...
Intrinsically disordered proteins (IDPs) lack stable three-dimensional structures, yet play vital roles in key biological processes, including signali...
Background Genome-wide association studies (GWAS) have identified numerous risk loci for Parkinson's disease, yet identifying causal genes and mechani...
The spatiotemporal progression of tau aggregates in neurodegenerative diseases like Alzheimer's follows the brain's structural connectome, yet a profo...
Discovery of sensitive and biologically grounded biomarkers is essential for early detection and monitoring of Alzheimer's disease (AD). Structural MR...
Deep learning models for neuroimaging increasingly rely on large architectures, making efficiency a persistent concern despite advances in hardware. T...
A desirable property of any deployed artificial intelligence is generalization across domains, i.e. data generation distribution under a specific acqu...