Dementia

Tau reduction counteracts transcriptomic and behavioral abnormalities in an Alzheimer amyloid model

Alzheimer's disease (AD) causes amyloid formation, neuritic dystrophy, gliosis, synapse loss, behavioral abnormalities, and weight loss. 5xFAD transgenic mice simulate these alterations. To further investigate overall tau reduction as a therapeutic strategy for AD-related abnormalities, we compared 5xFAD mice carrying 2, 1, or 0 Mapt alleles encoding endogenous wildtype tau. Behavioral alterations...

PatTree: a novel approach for automated creation of multimodal, graph-based patient representations for medical classification tasks

Access to holistic, multimodal data improves the performance of Artificial Intelligence (AI) in medical classification tasks compared to utilizing single modalities or data sources. However, the inherent heterogeneity and complexity of clinical real-world data pose significant challenges to structured data analysis and AI application. This heterogeneity includes missing values, multiple time point...

GoT-CD: Graph-of-Thoughts Causal Discovery and the Fragility of Post-hoc Path-Specific Fairness Audits

Causal discovery recovers directed structure from observational data and is increasingly used in clinical settings to support mechanism reasoning and ...

Human-Centered Reflections on Care Robots: A Comparative Study of Caregiver Perspectives

Care robots are increasingly being introduced into healthcare settings, raising important questions about their acceptance and ethical implementation....

A Neurosymbolic Approach for Explainable Early Diagnosis of Alzheimer's Disease

Identifying reliable Alzheimer's disease (AD) markers typically requires manual, labor-intensive transcription and expert analysis, limiting its scale...

Technological Advances in Detecting and Managing Cognitive Impairment in Older Adults: Trends, Challenges, and Future Directions

As populations age, cognitive decline from mild cognitive impairment (MCI) to dementia is a defining health challenge of the coming decades, yet routi...

TIER-MoE: Trust-Informed Expert Routing via Conditional Modality Risk for Multimodal Fusion in Biomedical Classification

The promise of multimodal fusion lies in combining complementary sources of evidence, yet more evidence does not always yield a better prediction. Rec...

Generalizability of EEG-Based Dementia Classifiers: A Multicenter study of Alzheimer, MCI, and FTD

EEG-based machine learning shows promise for neurodegenerative disease classification, but robustness to sample imbalance, center heterogeneity, and v...

Fine-Grained Emotional Characterization of Dementia Caregivers in Online Support Communities Using Large Language Models

Background: Dementia caregiving carries substantial emotional and psychological consequences, but most evidence comes from structured surveys and inte...

An Attention-Based Framework for Alzheimers Disease Classification Using Resting-State fMRI

Accurate identification of Alzheimers disease (AD) using resting-state functional magnetic resonance imaging (rs-fMRI) remains challenging due to the ...

Edge-Based ADL Recognition Using Room-Specialized Mixture-of-Experts

Activities of daily living (ADLs) provide important indicators of functional decline in people living with dementia, motivating the need for continuou...

Disentangling Acoustic Cues in Alzheimer's Pathology and Perception: The Roles of Language and Gender

Acoustic biomarkers show promise for detecting Alzheimer's Disease (AD), yet whether the cues driving diagnostic AI align with those salient to human ...

Stress-Testing EEG Foundation Models for Clinical Decoding: Dataset Identity and Targeted Negative Controls

Pretrained EEG foundation models are increasingly proposed for clinical decoding, but their transfer across populations and robustness to negative con...

Validation of clinical diagnosis and machine learning classification of cognitive impairment

INTRODUCTION: Cognitive syndrome diagnosis (Normal, Mild Cognitive Impairment (MCI), Dementia) is important for summarizing disease status and predict...

Encoding Discordance in the Alzheimer's Disease A/T/N Framework

INTRODUCTION: The biomarker-based amyloid/ tau/ neurodegeneration (A/T/N) framework has become a popular staging method for Alzheimer's disease (AD) r...

Multi-model Segmentation and Morphometric Quantification of Cerebral Amyloid Angiopathy in Alzheimer's Disease Whole Slide Histopathology Images

Introduction: Cerebral amyloid angiopathy (CAA) is characterized by amyloid-beta deposition in cortical and leptomeningeal vessels and associated with...

When does more data help? Spectral Geometry and Scaling Laws in MRI Transformers

Scaling laws describe how model performance improves as the amount of training data increases, and recent theories such as the zeta law suggest that s...

Death in People with Down syndrome: Mortality statistics and novel predictors in US Medicaid and Medicare enrolled adults.

People with Down syndrome have higher age-specific mortality rates compared to the general population as well as peers with other intellectual and dev...

What Do Persistent Misclassifications Tell Us About Alzheimer's Disease Detection using Structural MRI?

Deep learning classifiers applied to structural MRI (sMRI) have achieved high performance in detecting Alzheimer's Disease (AD), yet systematic invest...

Calibrated Alzheimer's Conversion Risk in Mild Cognitive Impairment: Persistent Homology of Clinical Trajectories with Conformal Guarantees

Background. Predicting conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) is central to trial enrichment and care planning, y...