Neurology

Time-frequency embedding with contrastive pre-training allows sub-second seizure detection.

OBJECTIVE: Rapid and accurate detection of electrographic seizures is critical for both clinical diagnosis and neuroscience research. Although seizure identification is commonly performed in the time domain, analysis in the time-frequency domain provides a more comprehensive representation of seizure characteristics. APPROACH: In this study, we present a 3D convolutional neural network (CNN) that ...

Clinically interpretable prediction models of stroke functional outcomes: A national cohort study of adults in inpatient rehabilitation facilities in the US.

OBJECTIVE: To predict self-care and mobility function at discharge from inpatient rehabilitation for adults with stroke using only variables from the Inpatient Rehabilitation Facility Patient Assessment Instrument (IRF-PAI), which are mandated in the United States by the Centers for Medicare and Medicaid Services. DESIGN: Retrospective cohort study. SETTING: Inpatient rehabilitation facilities (IR...

Pharmacological evidence for propagation dynamics of TMS-evoked potentials in the human brain.

BACKGROUND: Transcranial magnetic stimulation-evoked potentials (TEPs) propagate from the stimulation site to distributed brain networks, with early p...

Digital and Smart Technologies for Early Pressure Injury Detection and Prevention in Stroke and Mobility-Impaired Patients: A Scoping Review.

BACKGROUND: Pressure injuries remain a major complication among stroke and other mobility-impaired populations. Digital and smart technologies are inc...

Identification of critical brain regions for young adults with obesity and their relationships with impulsivity using machine learning based on neuroanatomical features.

BACKGROUND: Prior obesity neuroimaging studies used univariate methods and small samples, limiting reproducibility. Employing a large-scale dataset an...

Machine Learning-Based Classification of Neuroblastoma Risk Groups and MYCN Status.

BACKGROUND: Artificial intelligence (AI)-based methods have demonstrated considerable promise in identifying histological features in whole slide imag...

Identification of novel PKR inhibitory chemotypes via integrated molecular modelling and machine learning.

Interferon-inducible RNA-dependent protein kinase (PKR) is an emerging therapeutic target involved in cancer, neurodegeneration, and inflammatory diso...

Diagnostic decision-making, vertebral augmentation, and osteoporosis therapy in vertebral compression fractures: a narrative review.

Vertebral compression fractures (VCFs) represent the most prevalent osteoporotic fracture and constitute a growing cause of morbidity, mortality, and ...

Time-Domain HRV Metrics as Predictors of Concussion Recovery in Adolescents: A Boosted Tree Approach.

BACKGROUND: Concussions in adolescents, especially in sports, represent a major public health issue due to prolonged recovery and diagnostic challenge...

Manual and automated capture of analgesic-responsive facial pain behaviors of unrestrained mice in a trigeminal neuralgia model.

Trigeminal neuralgia (TN), a devastating neuropathic pain condition, profoundly affects human well-being. Despite an initial response to carbamazepine...

Accelerated Brain Aging in Type 1 Diabetes Across Painful and Painless Peripheral Neuropathy: MRI-Based Brain Age Estimates From Deep Learning.

Accelerated brain aging has been reported in diabetes, but its links with diabetic peripheral neuropathy (DPN) and neuropathic pain remain unclear. We...

Brainstem Raphe Nuclei and Their Serotonergic Neurons: An Integrative Review of Distribution, Function and Projection.

Serotonergic neurons in the raphe nuclei of the brainstem play a central role in a wide range of physiological and psychological processes. These neur...

Thrombus imaging features influencing the choice of first-line thrombectomy strategy: an international survey of neurointerventionists.

INTRODUCTION: Endovascular thrombectomy (EVT) is the standard of care for large vessel occlusion stroke, but the optimal first-line strategy remains d...

Multicenter Validation of an AI-Based CTA Tool for Anterior Circulation Large Vessel Occlusion Detection.

BACKGROUND: Rapid identification of anterior circulation large vessel occlusions (LVOs) is critical for timely mechanical thrombectomy in acute ischem...

Accelerating Focused Ultrasound Modeling in Heterogeneous Spinal Cord Anatomy With Vision Transformer Operator Networks.

OBJECTIVE: The purpose of this work is to develop a data-driven framework for real-time prediction of focused ultrasound pressure fields in the spinal...

Directed graph neural networks with partial directed coherence for seizure prediction and epileptogenic network characterization.

While electroencephalography (EEG) analyses using undirected connectivity are well-established for seizure prediction and epileptogenic zone (EZ) netw...

Rational drug design for Alzheimer's disease: from approved therapies to next-generation clinical candidates and AI-guided innovation.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by multifactorial pathology, including amyloid-β (Aβ) aggregation, ...

Spatial-Spectral Fusion Enables Drug Repositioning by Capturing Indirect and Long-Range Associations in Biological Networks.

MOTIVATION: Drug repositioning accelerates clinical translation by identifying new therapeutic indications for approved drugs. However, therapeutic as...

Integrating New Approach Methodologies and Artificial Intelligence to Advance Central Nervous System Toxicity Prediction: Lessons from Preclinical and Clinical Case Studies.

Central nervous system (CNS) toxicities remain a major cause of drug attrition and represent a persistent challenge in predicting neurological risk du...

Multimodal artificial intelligence for prostate cancer imaging: workflow-relevant fusion of mpMRI, PSMA PET, ultrasound, and clinical data for diagnosis, local staging, and treatment personalization.

BACKGROUND: Prostate cancer imaging is inherently multimodal, yet many AI tools remain single-modality and therefore misaligned with real-world abdomi...