Neurology

Camera-Agnostic Autonomous Diagnosis of Glaucomatous Optic Neuropathy using Macular Fundus Imaging and Machine Learning

Abstract Purpose: Glaucoma, a leading cause of irreversible vision loss, often remains undiagnosed due to its asymptomatic progression and the limitations of existing screening methods. This study aimed to validate an artificial intelligence machine learning algorithm for the camera-agnostic detection of glaucomatous optic neuropathy using macula-centered fundus images. Methods: Data were collecte...

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

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. In this study, we present a 3D convolutional neural network (CNN) that incorporates a traina...

Neural Spectral Prediction for Structure Elucidation with Tandem Mass Spectrometry

Structural elucidation using untargeted tandem mass spectrometry (MS/MS) has played a critical role in advancing scientific discovery. However, differ...

From Thought to Speech: Integrating a Low-Cost Electroencephalography Device with AI to Decode Neural Language Signals in Amyotrophic Lateral Sclerosis Patients

Purpose: Nearly all amyotrophic lateral sclerosis (ALS) patients develop dysarthria, with many progressing to anarthria and global expressive communic...

The Vesicular Glutamate Transporter Modulates Sex and Region-Specific Differences in Dopaminergic Neuron α-Synuclein Toxicity by Modifying Cytosolic Dopamine Levels

Parkinson's disease disproportionately affects males; however, the cause of this sex difference is unknown. We found that expressing mutant -synuclein...

Integrating Acoustic, Prosodic, and Phonological Features for Automatic Alzheimer's Detection

Early and accurate diagnosis of Alzheimer's Disease (AD) is critical for effective intervention. While previous studies have explored speech-based bio...

Anatomically Guided Latent Diffusion for Brain MRI Progression Modeling

Accurately modeling longitudinal brain MRI progression is crucial for understanding neurodegenerative diseases and predicting individualized structura...

The Pictorial Cortex: Zero-Shot Cross-Subject fMRI-to-Image Reconstruction via Compositional Latent Modeling

Decoding visual experiences from human brain activity remains a central challenge at the intersection of neuroscience, neuroimaging, and artificial in...

A Computer Vision Hybrid Approach: CNN and Transformer Models for Accurate Alzheimer's Detection from Brain MRI Scans

Early and accurate classification of Alzheimers disease (AD) from brain MRI scans is essential for timely clinical intervention and improved patient o...

EEG-Titans: Long-Horizon Seizure Forecasting via Dual-Branch Attention and Neural Memory

Accurate epileptic seizure prediction from electroencephalography (EEG) remains challenging because pre-ictal dynamics may span long time horizons whi...

Sleep dynamics and epileptogenesis following Kainic acid in epilepsy-susceptible (DBA/2J) and epilepsy-resistant (C57BL/6) mice

Susceptibility to epileptogenesis varies in humans and outbred mouse strains. We hypothesized that baseline sleep abnormalities increase susceptibilit...

ConvMambaNet: A Hybrid CNN-Mamba State Space Architecture for Accurate and Real-Time EEG Seizure Detection

Epilepsy is a chronic neurological disorder marked by recurrent seizures that can severely impact quality of life. Electroencephalography (EEG) remain...

Digital FAST: An AI-Driven Multimodal Framework for Rapid and Early Stroke Screening

Early identification of stroke symptoms is essential for enabling timely intervention and improving patient outcomes, particularly in prehospital sett...

ARMARecon: An ARMA Convolutional Filter based Graph Neural Network for Neurodegenerative Dementias Classification

Early detection of neurodegenerative diseases such as Alzheimer's Disease (AD) and Frontotemporal Dementia (FTD) is essential for reducing the risk of...

Transmission Dynamics of Eastern Equine Encephalitis Infection Rates: The Role of Avian Host Stage and Differential Mosquito Exposure

Eastern equine encephalitis virus (EEEV) is a deadly arboviral pathogen with 30% severe case fatality. EEEV exhibits pronounced 2-3 year cyclical outb...

Graph Neural Network Reveals the Local Cortical Morphology of Brain Aging in Normal Cognition and Alzheimers Disease

Estimating brain age (BA) from T1-weighted magnetic resonance images (MRIs) provides a useful approach to map the anatomic features of brain senescenc...

Depression Detection Based on Electroencephalography Using a Hybrid Deep Neural Network CNN-GRU and MRMR Feature Selection

This study investigates the detection and classification of depressive and non-depressive states using deep learning approaches. Depression is a preva...

Explainable histomorphology-based survival prediction of glioblastoma, IDH-wildtype

Glioblastoma, IDH-wildtype (GBM-IDHwt) is the most common malignant brain tumor. Histomorphology is a crucial component of the integrated diagnosis of...

Transformer-based EEG Source Imaging Enables Robust Localization of Pathological High-Frequency Oscillations in Epilepsy

ObjectiveHigh-frequency oscillations (HFOs) are highly specific biomarkers of epileptogenic tissue, yet their noninvasive localization remains challen...

Non-reproducibility of wearable accelerometer methods in protective association between physical activity and cardiovascular disease: a cohort study.

BackgroundThe selection of accelerometer processing methods may influence the shape of the dose-response association between wearable-measured physica...