Geriatrics

Alzheimer's Disease

Latest AI and machine learning research in alzheimer's disease for healthcare professionals.

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Geriatrics Subcategories: Alzheimer's Disease Medicare
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Alzheimer’s Disease (AD), a progressive neurodegenerative condition of cognitive decline, presents formidable challenges to patients, caregivers, and healthcare systems. Early identification is essential for successful intervention, but traditional diagnosis requires expensive neuroimaging and lengthy clinical assessments, which compromise access. This study proposes a semi-supervised machine lear...

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 introduce PRISM-ML (PRecision-medicine using Interpretable Systems and Multiomics with Machine Learning), an open-source integrated analysis pipeline that combines interpretable machine learning with systems biology and electronic health record (EHR...

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...

Structure-based Generation of a Secondary Nucleation Inhibitor in α-Synuclein Aggregation Using a Conditional Diffusion Model

The process of α-synuclein aggregation results in the formation of amyloid fibrils, which accumulate in the brain of patients affected by Parkinson’s ...

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...

Disease-specific tau polymorphs define unique protein interaction networks across proteinopathies

Tau protein aggregates exhibit distinct conformations across tauopathies, but their disease-specific protein interactions remain poorly understood. He...

Claustrum volume in humans – lifespan trajectory and effect of age, hemisphere, and sex

The human claustrum is a bilateral, thin, irregularly shaped gray matter structure located between the striatum and insula. While previous research de...

Frequency-Aware Interpretable Deep Learning Framework for Alzheimer’s Disease Classification Using rs-fMRI

Gaining insight into the spectral and temporal alterations in brain connectivity associated with Alzheimer’s disease (AD) may offer pathways toward mo...

Evaluation of Deep Learning Algorithms to Predict Multiple Dementia-Related Neuropathologies from Brain MRI, Clinical and Genetic Data

Alzheimer’s disease and related dementias (ADRD) involve overlapping neurodegenerative and vascular pathologies—such as amyloid-β (Aβ), tau, cerebral ...

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