Alzheimer's Disease

NeuroFM: Toward Precision Neuroimaging with Foundation Models for Individualized Brain Health Estimation

Precision neuroimaging aims to deliver individualized assessments of brain health, yet a single structural MRI does not yield a multidimensional, quantitative summary of an individual's current health or future risk. Existing approaches optimize task-specific objectives, yielding representations entangled with cohort- or disease-specific signals rather than capturing biologically grounded patterns...

PHENOCAUZ: Linking Human Symptoms, Drug Side Effects and Efficacy to Their Molecular Causes Using Mendelian Disease Biology

Human diseases and adverse drug reactions are ultimately recognized through clinical symptoms, yet the molecular determinants of most symptoms remain unknown. To address this key issue, we present PHENOCAUZ, a computational framework that links symptoms to their causative proteins by integrating Mendelian phenotype - gene relationships with molecular features of proteins. Starting from symptom ann...

Longitudinal Boundary Sharpness Coefficient Slopes Predict Time to Alzheimer's Disease Conversion in Mild Cognitive Impairment: A Survival Analysis Using the ADNI Cohort

Predicting whether someone with mild cognitive impairment (MCI) will progress to Alzheimer's disease (AD) is crucial in the early stages of neurodegen...

EEG-SSFormer: Towards a Robust Mamba-Based Architecture for Dementia Detection from Resting State Electroencephalography

Resting-state electroencephalography (rs-EEG) offers a cost effective and portable alternative to conventional neuroimaging for dementia screening, ye...

AD-Reasoning: Multimodal Guideline-Guided Reasoning for Alzheimer's Disease Diagnosis

Alzheimer's disease (AD) diagnosis requires integrating neuroimaging with heterogeneous clinical evidence and reasoning under established criteria, ye...

A deep-learning based biomarker of systemic cellular senescence burden to predict mortality and health outcomes

Introduction: The accumulation of senescent cells is a recognized hallmark of biological aging and is associated with the onset of multiple chronic me...

Cerebra: A Multidisciplinary AI Board for Multimodal Dementia Characterization and Risk Assessment

Modern clinical practice increasingly depends on reasoning over heterogeneous, evolving, and incomplete patient data. Although recent advances in mult...

A Multidisciplinary AI Board for Multimodal Dementia Characterization and Risk Assessment

Modern clinical practice increasingly depends on reasoning over heterogeneous, evolving, and incomplete patient data. Although recent advances in mult...

Causal differential expression analysis under unmeasured confounders with causarray

Advances in single-cell sequencing and CRISPR technologies have enabled detailed case-control comparisons and experimental perturbations at single-cel...

Impact of automatic speech recognition quality on Alzheimer's disease detection from spontaneous speech: a reproducible benchmark study with lexical modeling and statistical validation

Early detection of Alzheimer's disease from spontaneous speech has emerged as a promising non-invasive screening approach. However, the influence of a...

OpenScientist: evaluating an open agentic AI co-scientist to accelerate biomedical discovery

Background: Advances in medicine depend on analyzing large and complex data sources, but discovery is partly constrained by the limited time and domai...

3D MRI-Based Alzheimer's Disease Classification Using Multi-Modal 3D CNN with Leakage-Aware Subject-Level Evaluation

Deep learning has become an important tool for Alzheimer's disease (AD) classification from structural MRI. Many existing studies analyze individual 2...

Tabular LLMs for Interpretable Few-Shot Alzheimer's Disease Prediction with Multimodal Biomedical Data

Accurate diagnosis of Alzheimer's disease (AD) requires handling tabular biomarker data, yet such data are often small and incomplete, where deep lear...

Multimodal Molecular Mapping of the Vasculature in Human Cortex Reveals Lipid Markers of Cerebral Amyloid Angiopathy

Cerebral amyloid angiopathy (CAA) commonly co-occurs with Alzheimer's disease (AD), yet the molecular changes that accompany vascular beta-amyloid dep...

Federated Learning for Privacy-Preserving Medical AI

This dissertation investigates privacy-preserving federated learning for Alzheimer's disease classification using three-dimensional MRI data from the ...

Probabilistic Joint and Individual Variation Explained (ProJIVE) for Data Integration

Collecting multiple types of data on the same set of subjects is common in modern scientific applications including, genomics, metabolomics, and neuro...

Paper Title: LoV3D: Grounding Cognitive Prognosis Reasoning in Longitudinal 3D Brain MRI via Regional Volume Assessments

Longitudinal brain MRI is essential for characterizing the progression of neurological diseases such as Alzheimer's disease assessment. However, curre...

From General-Purpose to Disease-Specific Features: Aligning LLM Embeddings on a Disease-Specific Biomedical Knowledge Graph for Drug Repurposing

Identifying new therapeutic uses for existing drugs is a major challenge in biomedicine, especially for complex neurodegenerative conditions such as A...

Characterizing EEG Spectro-Temporal Variability Signatures in Alzheimer's and Parkinson's Disease

We present an EEG-based approach to characterize disease-related spectro-temporal signatures in Alzheimer's disease (AD) and Parkinson's disease (PD)....

YOLO-NAS-Bench: A Surrogate Benchmark with Self-Evolving Predictors for YOLO Architecture Search

Neural Architecture Search (NAS) for object detection is severely bottlenecked by high evaluation cost, as fully training each candidate YOLO architec...