Alzheimer's Disease

GMN4AD: Graph Matching Network for Alzheimer's Disease Diagnosis with Test-Time Domain Adaptation using Multi-centered Structure Magnetic Resonance Imaging

Alzheimer's Disease (AD) is a progressive neurodegenerative disorder that affects millions of older adults, with prevalence expected to rise significantly in the coming years. Early diagnosis, particularly during the mild cognitive impairment (MCI) stage, is critical for timely intervention. Structural Magnetic Resonance Imaging (sMRI) has emerged as a key modality for detecting AD-related brain c...

MipSScs: Artificial neural network-based data integration of 2D/3D single-cell spatial RNA sequence data from virus-infected human cerebral organoids

There is interest in the use of recent single-cell spatial transcriptomic technologies to gain biological insights into disease mechanisms. Previously, we characterized the use of herpes simplex virus 1 (HSV-1) induced neuroinflammation in 2D dissociated cells from human cerebral organoids (dcOrgs) to model molecular and transcriptomic readouts associated with Alzheimers disease (AD). In this work...

TMO: ASYMMETRIC CROSS-MODAL ATTENTION FOR LEARNINGCELL-STATE-DEPENDENT REGULATORY LAGS FROM SINGLE-CELL MULTIOMIC DATA

Abstract Background: Single-cell multi-omics technologies simultaneously measure chromatin accessibility (ATAC) and gene expression (RNA), providing a...

End-to-End Machine Learning for Depressive State Classification via EEG and fNIRS

The escalating demand for mental healthcare, driven by rising societal stress, highlights the limitations of traditional psychiatric diagnostics. Conv...

Multimodal Ordinal Modeling of Alzheimer's Disease Severity Using Structural MRI and Clinical Data

Neurodegenerative diseases such as Alzheimer's disease (AD) require accurate and scalable tools for assessing disease severity, yet current clinical s...

Candidate Molecular Subtypes of Cognitive Resilience in Alzheimers Disease: A Multi-Cohort Machine Learning and Neuroimaging Study

Background: Cognitive resilience (CR) in Alzheimers disease (AD) refers to preserved cognitive function despite substantial AD pathology. Diverse biol...

Sleep EEG Signal Criticality as a Non-Invasive Predictor of Cognitive Decline in Dementia

Early detection of neurodegeneration remains a critical clinical challenge. This study investigates whether sleep EEG signal criticality, quantified v...

Transition-Based Digital Twin Modelling for Alzheimer's Disease under Sparse Longitudinal Data

Alzheimer's disease (AD) progression is highly heterogeneous and is typically observed through sparse and irregular longitudinal data, posing challeng...

Immediate to longer-term neurophysiological impact of acute neural network disruption

Despite substantial interest in how neural systems recover over time after acute neurological events, there is a dearth of longitudinal assessment fro...

EXHEART: A Fairness-Aware Explainable Stacked Ensemble for Cardiovascular Disease Classification with Cross-Instrument Disparity Attribution

Background: Machine learning models trained on population health surveys offer scalable tools for cardiovascular screening, but recurring methodologic...

Multilingual Detection of Alzheimer's Disease from Speech: A Cross-Linguistic Transfer Learning Approach

The development of multilingual Alzheimer's Disease Dementia (AD) detection models presents significant challenges due to the resource-intensive and t...

Cross-scale spatially-aware generative modeling of transcriptomic programs underlying neurodegenerative brain organization

Neurodegenerative disorders such as Alzheimer's disease exhibit highly organized patterns of regional brain vulnerability, yet the biological mechanis...

Predicting the timing of first sustained cognitive worsening in Alzheimer's disease using real-world clinical data and machine learning

Background: Cognitive assessments are sparsely documented in electronic health records (EHRs), limiting scalable detection of cognitive worsening in r...

Medication-Wide Association Study of Alzheimer's Disease and Related Dementias: Identifying Drug Candidates from Electronic Health Records through Explainable AI

Objective: Alzheimer's disease (AD) is a leading cause of death and disability, and treatment options for Alzheimer's disease and related dementias (A...

Multiplex Proteomics of Lewy Body Dementia Reveals Cerebrospinal Fluid Biomarkers of Clinical and Neuropathological Heterogeneity

Lewy body dementia (LBD), which encompasses Parkinson's disease dementia (PDD) and Dementia with Lewy bodies (DLB), lacks established biofluid markers...

Towards A Foundation Model for Clinical Voice Biomarkers

Vocal biomarkers, encompassing voice and speech, have largely been developed for individual conditions in isolation, limiting their generalizability a...

A Multi-Agent RAG Framework for Biomedical Literature Analysis

Background: The biomedical literature is expanding at an unprecedented rate, with over 4,000 new articles indexed on PubMed each day. Clinicians and r...

Comparing Pathway-Informed Polygenic Risk Score Strategies: A multi-cohort evaluation of Amyloid-β

Objective: To systematically evaluate pathway-informed polygenic risk score (PRS) strategies and determine which approaches most effectively leverage ...

Wearable and Interview-based Assessment of Psychological Risk in Alzheimers Caregivers: Machine Learning vs. Large Language Models

Spousal caregivers of individuals with Alzheimers disease and related dementias frequently experience elevated perceived stress, caregiver burden, and...

Automated quantification of cerebral microbleeds for ARIA-H monitoring in Aging and Alzheimer's Disease: A multicenter deep learning validation

We trained a self-configuring nnU-Net model for CMB segmentation in a heterogeneous multicenter sample (n=264), including 1.5T and 3T field strengths,...