Alzheimer's Disease

Adaptive Clinical-Aware Latent Diffusion for Multimodal Brain Image Generation and Missing Modality Imputation

Multimodal neuroimaging provides complementary insights for Alzheimer's disease diagnosis, yet clinical datasets frequently suffer from missing modalities. We propose ACADiff, a framework that synthesizes missing brain imaging modalities through adaptive clinical-aware diffusion. ACADiff learns mappings between incomplete multimodal observations and target modalities by progressively denoising lat...

Tau-BNO: Brain Neural Operator for Tau Transport Model

Mechanistic modeling provides a biophysically grounded framework for studying the spread of pathological tau protein in tauopathies like Alzheimer's disease. Existing approaches typically model tau propagation as a diffusive process on the brain's structural connectome, reproducing macroscopic patterns but neglecting microscale cellular transport and reaction mechanisms. The Network Transport Mode...

CRIMSON: A Clinically-Grounded LLM-Based Metric for Generative Radiology Report Evaluation

We introduce CRIMSON, a clinically grounded evaluation framework for chest X-ray report generation that assesses reports based on diagnostic correctne...

An Integrated Molecular Atlas of Alzheimer's Disease

Alzheimer's disease (AD) is a complex neurodegenerative disorder with multifactorial etiology and widespread molecular manifestations. Investigating m...

Automated machine learning of echocardiographic strain enables identification of early myocardial changes in pre-symptomatic TTR carriers

Objectives: To identify unique echocardiographic signatures associated with TTR+ carrier status preceding onset of cardiac amyloidosis. Background: Ca...

Aβ-Overlapping Ectodomain Binding of the Clinical-Stage TREM2 Agonist VG-3927

Triggering receptor expressed on myeloid cells 2 (TREM2) is a microglial immune receptor genetically and functionally linked to Alzheimers disease (AD...

Evaluating a Locally Deployed 20-Billion Parameter Large Language Model for Automated Abstract Screening in Systematic Reviews

Abstract Background: Systematic reviews (SRs) are essential for evidence-based medicine but require extensive time and resources for abstract screenin...

Streamlining Eligibility Assessment for Alzheimers Disease-Modifying Therapies: Prediction of MMSE Scores Using the Digital Clock and Recall

Introduction: The eligibility of anti-amyloid disease-modifying therapies (DMTs) and their integration into clinical practice in some institutions req...

Longitudinal Impact of NLP-Augmented Clinical Decision Support on Cognitive Decline Detection in German Geriatric Primary Care: A Dynamic Panel Data Analysis Using System GMM Estimation

Background: Cognitive decline and dementia represent major public health challenges in aging populations. Natural language processing (NLP)-augmented ...

Multi-Omics Integration of Transcriptomics and Metabolomics with Machine Learning Uncovers Novel Risk Factors for Alzheimer's disease

Background: Alzheimer's disease (AD) is a neurodegenerative disorder characterized by cognitive decline, memory impairment, and functional deteriorati...

MIRAGE: Knowledge Graph-Guided Cross-Cohort MRI Synthesis for Alzheimer's Disease Prediction

Reliable Alzheimer's disease (AD) diagnosis increasingly relies on multimodal assessments combining structural Magnetic Resonance Imaging (MRI) and El...

The Combinatorial Capacity and Robustness of Hierarchical Concept Coding in the Human Medial Temporal Lobe

The human brain encodes a virtually infinite repertoire of semantic concepts using a finite number of neurons, a feat that defies the capacity limits ...

DOCFORGE-BENCH: A Comprehensive Benchmark for Document Forgery Detection and Analysis

We present DOCFORGE-BENCH, the first unified zero-shot benchmark for document forgery detection, evaluating 14 methods across eight datasets spanning ...

Align-cDAE: Alzheimer's Disease Progression Modeling with Attention-Aligned Conditional Diffusion Auto-Encoder

Generative AI framework-based modeling and prediction of longitudinal human brain images offer an efficient mechanism to track neurodegenerative progr...

MINT: Multimodal Imaging-to-Speech Knowledge Transfer for Early Alzheimer's Screening

Alzheimer's disease is a progressive neurodegenerative disorder in which mild cognitive impairment (MCI) marks a critical transition between aging and...

DisQ-HNet: A Disentangled Quantized Half-UNet for Interpretable Multimodal Image Synthesis Applications to Tau-PET Synthesis from T1 and FLAIR MRI

Tau positron emission tomography (tau-PET) provides an in vivo marker of Alzheimer's disease pathology, but cost and limited availability motivate MRI...

Disease Progression and Subtype Modeling for Combined Discrete and Continuous Input Data

Disease progression modeling provides a robust framework to identify long-term disease trajectories from short-term biomarker data. It is a valuable t...

RelA-Diffusion: Relativistic Adversarial Diffusion for Multi-Tracer PET Synthesis from Multi-Sequence MRI

Multi-tracer positron emission tomography (PET) provides critical insights into diverse neuropathological processes such as tau accumulation, neuroinf...

EMAD: Evidence-Centric Grounded Multimodal Diagnosis for Alzheimer's Disease

Deep learning models for medical image analysis often act as black boxes, seldom aligning with clinical guidelines or explicitly linking decisions to ...

LERD: Latent Event-Relational Dynamics for Neurodegenerative Classification

Alzheimer's disease (AD) alters brain electrophysiology and disrupts multichannel EEG dynamics, making accurate and clinically useful EEG-based diagno...