Neurology

Robust and Clinically Reliable EEG Biomarkers: A Cross Population Framework for Generalizable Parkinson's Disease Detection

Developing robust and clinically reliable EEG biomarkers requires evaluation frameworks that explicitly address cross population generalization in multi site settings such as Parkinsons disease (PD) detection. Models trained under i.i.d. assumptions often capture population specific artifacts rather than disease relevant neural structure, leading to poor generalization across clinical cohorts. EEG...

Task-guided Spatiotemporal Network with Diffusion Augmentation for EEG-based Dementia Diagnosis and MMSE Prediction

Patients with dementia typically exhibit cognitive impairment, which is routinely assessed using the Mini-Mental State Examination (MMSE). Concurrently, their underlying neurophysiological abnormalities are reflected in Electroencephalography (EEG), providing a basis for joint modeling. However, traditional multi-task approaches suffer from feature entanglement, which leads to inter-task interfere...

Monocular Depth Estimation via Neural Network with Learnable Algebraic Group and Ring Structures

Monocular depth estimation (MDE) has witnessed remarkable progress driven by Convolutional Neural Networks and transformer-based architectures. Howeve...

BandRouteNet: An Adaptive Band Routing Neural Network for EEG Artifact Removal

Electroencephalography (EEG) is highly susceptible to artifact contamination, such as electrooculographic (EOG) and electromyographic (EMG) interferen...

Decoding the phenomenology of spontaneous thought using large language-model ratings on verbal retrospective free reports

Spontaneous thoughts constitute most of everyday inner experience, yet long-standing methodological challenges obscure a thorough exploration of their...

Integrative Clinical-Molecular Modeling Identifies LRRN4CL as a Determinant of Structural and Functional Myocardial Improvement

Background: Mechanical ventricular unloading and systemic circulatory support with left ventricular assist devices (LVADs) enable myocardial recovery ...

Prognosis of stroke subtypes in whole population health systems data: a matched cohort study

Background Outcome after stroke varies according to stroke subtype by location, but healthcare systems data studies do not include subtyping informati...

Multi-Modal Deep Learning Integrates Spatial Topologies and Sequential Motifs to Identify Class I HDAC Inhibitors as Pan-Cancer Therapeutics

The molecular characterization of human solid growths has introduced immense genomic complexity and intra-tumoral diversification. Converting these de...

Structure-Guided Diffusion Model for EEG-Based Visual Cognition Reconstruction

Objective: Decoding visual information from electroencephalography (EEG) is an important problem in neuroscience and brain-computer interface (BCI) re...

Generative Modeling of Neurodegenerative Brain Anatomy with 4D Longitudinal Diffusion Model

Understanding and predicting the progression of neurodegenerative diseases remains a major challenge in medical AI, with significant implications for ...

Image-grounded encoding models reveal distinct temporal profiles of naturalistic object and scene processing in the human brain

The human brain processes large amounts of complex visual information in order to effectively interact with its environment. It is well established th...

Predictive Cellular Signatures from Live Human Motor Neurons Distinguish TDP-43 ALS and Enable ALS Subtype Stratification

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by the progressive, rapid deterioration of motor neurons (MNs)...

Improving clinical interpretability of linear neuroimaging models through feature whitening

Linear models are widely used in computational neuroimaging to identify biomarkers associated with brain pathologies. However, interpreting the learne...

Subject-Aware Multi-Granularity Alignment for Zero-Shot EEG-to-Image Retrieval

Zero-shot EEG-to-image retrieval aims to decode perceived visual content from electroencephalography (EEG) by aligning neural responses with pretraine...

Predictive Modeling of Natural Medicinal Compounds for Alzheimer Disease Using Cheminformatics

The most common cause of dementia is Alzheimer disease, a progressive neurodegenerative disorder affecting older adults that gradually impairs memory,...

Parkinson's Disease Detection via Self-Supervised Dual-Channel Cross-Attention on Bilateral Wrist-Worn IMU Signals

Parkinson's disease (PD) is a chronic neurodegenerative disease. It shows multiple motor symptoms such as tremor, bradykinesia, postural instability, ...

Deep learning based Non-Rigid Volume-to-Surface Registration for Brain Shift compensation Using Point Cloud

Soft-tissue deformation remains a major limitation in image-guided neurosurgery, where intra-operative anatomy can deviate substantially from pre-oper...

MESA: A Training-Free Multi-Exemplar Deep Framework for Restoring Ancient Inscription Textures

Ancient inscriptions frequently suffer missing or corrupted regions from fragmentation, erosion, or other damage, hindering reading, and analysis. We ...

STEP-PD: Stage-Aware and Explainable Parkinson's Disease Severity Classification Using Multimodal Clinical Assessments

Parkinson's disease (PD) is a progressive disorder in which symptom burden and functional impairment evolve over time, making severity staging essenti...

CLIMB: Controllable Longitudinal Brain Image Generation using Mamba-based Latent Diffusion Model and Gaussian-aligned Autoencoder

Latent diffusion models have emerged as powerful generative models in medical imaging, enabling the synthesis of high quality brain magnetic resonance...