Dementia

RealDiffFusionNet: Neural Controlled Differential Equation Informed Multi-Head Attention Fusion Networks for Disease Progression Modeling Using Real-World Data

This paper presents a novel deep learning-based approach named RealDiffFusionNet incorporating Neural Controlled Differential Equations (Neural CDE) - time series models that are robust in handling irregularly sampled data - and multi-head attention to align relevant multimodal context (image data, time invariant data, etc.) at each time point. Long short-term memory (LSTM) models were also used...

Denoising 7T Structural MRI with Conditional Generative Diffusion Models

7T MRI offers ultra-high resolution and improved sensitivity for iron deposition in neurodegenerative disorders, but commonly used acquisitions are long and hence challenging, especially for elderly subjects. Efficiently denoising a short acquisition to achieve the image quality of a longer acquisition would be of translational benefit. We introduce a conditional diffusion model derived from gener...

ConvNeXt-Driven Detection of Alzheimer’s Disease: A Benchmark Study on Expert-Annotated AlzaSet MRI Dataset Across Anatomical Planes

Alzheimer’s disease (AD) is a leading worldwide cause of cognitive impairment, necessitating accurate, inexpensive diagnostic tools to enable early re...

Biological Database Mining for LLM-Driven Alzheimer’s Disease Drug Repurposing

This study presents a software pipeline that leverages LLMs to apply knowledge stored in natural language (such as in pharmacological texts) and ontol...

Functional Connectome of Superagers Reveals Early Markers of Resilience and Vulnerability to Alzheimer’s Disease

As populations age, identifying the neurobiological basis of cognitive resilience is critical for delaying or preventing Alzheimer’s disease (AD). Whi...

Listening Beyond The Labels

Alzheimer’s Disease (AD), a progressive neurodegenerative condition of cognitive decline, presents formidable challenges to patients, caregivers, and ...

Integrating explainable AI with multiomics systems biology and EHR data mining for personalized drug repurposing in Alzheimer’s disease

Alzheimer’s disease (AD) is characterized by region- and patient-specific molecular heterogeneity, which hinders therapeutic design. In this study, we...

Replacement of a single residue in an antibody completely abolishes cognate antigen binding, as predicted by theoretical methods

Structural insights into the interaction between antibodies and antigens at the atomic level are pivotal for understanding the molecular mechanisms of...

Uncertainty in Deep Learning for EEG under Dataset Shifts

As artificial intelligence (AI) is increasingly integrated into medical diagnostics, it is essential that predictive models provide not only accurate ...

Pharmacological potentiation of Nav1.1 channels in interneurons mitigates tau depositions and neuronal death in a mouse model of neurodegenerative dementias

Epileptiform discharges and neuronal hyperexcitability are key pathophysiological features of Alzheimer’s disease and related tauopathies. We previous...

Comparative Analysis of Diffusion Models for Enhancing Alzheimer’s Disease Classification

Early and accurate detection of Alzheimer’s disease (AD) is vital for timely intervention and better patient outcomes. However, training machine learn...

Frequency bands EEG Biomarkers for Dementia using Graph Neural Networks

We introduce a simple and interpretable model for classification of electroencephalography (EEG) signals. Our focus essentially is on using deep learn...

Neural Network-Enhanced Investigation of Ferroptosis and Druggability in Early-Onset Alzheimer’s Disease

Alzheimer’s disease (AD) is a complex neurodegenerative disorder which is multifactorial in nature. Some of its characteristics are slow cognitive dec...

ROSMAP-Compass: a data-harmonised, AI-ready atlas of 22 million single nuclei from the ROSMAP cohort

The Religious Orders Study and Memory and Aging Project (ROSMAP) cohort has generated the world’s most comprehensive single-cell transcriptomic resour...

An Explainable Web-Based Diagnostic System for Alzheimer’s Disease Using XRAI and Deep Learning on Brain MRI

Background Alzheimer’s disease (AD) is a progressive neurodegenerative condition marked by cognitive decline and memory loss. Despite advancements in ...

In Silico Design of APOE ɛ4 Interaction Inhibitor Peptides for Alzheimer’s Disease

Protein-protein interactions (PPIs) are essential for cellular functions, and their aberrant formation contributes to neurodegenerative diseases. Alzh...

Alzheimer’s subtypes A supervised, unsupervised, multimodal, multilayered embedded recursive (SUMMER) AI study

Since Alzheimer’s disease (AD) is a heterogeneous disease, different subtypes may have distinct biological, genetic, and clinical characteristics, req...

Graph-Based Modeling of Alzheimer’s Protein Interactions via Spiking Neural, Hyperdimensional Encoding, and Scalable Ray-Based Learning

This study introduces a novel computational framework for predicting protein-protein interactions (PPIs) in Alzheimer’s disease by integrating biologi...

An Open-Source Deep Learning-Based Toolbox for Automated Auditory Brainstem Response Analyses (ABRA)

Hearing loss is a pervasive global health challenge with profound impacts on communication, cognitive function, and quality of life. Recent studies ha...

AmyloDeep: pLM-based ensemble model for predicting amyloid propensity from the amino acid sequence

Amyloids are predominantly β-sheet-rich, stable protein structures that can maintain their presence in the human body for multiple years. Amyloid prot...