Neurology

Dementia

Latest AI and machine learning research in dementia for healthcare professionals.

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Dynamic and Static Structure-Function Coupling With Machine Learning for the Early Detection of Alzheimer's Disease.

The progression of Alzheimer's disease (AD) involves complex changes in brain structure and function...

Evaluating Traditional, Deep Learning and Subfield Methods for Automatically Segmenting the Hippocampus From MRI.

Given the relationship between hippocampal atrophy and cognitive impairment in various pathological ...

Predicting explainable dementia types with LLM-aided feature engineering.

MOTIVATION: The integration of Machine Learning and Artificial Intelligence (AI) into healthcare has...

A deep-learning retinal aging biomarker for cognitive decline and incident dementia.

INTRODUCTION: The utility of retinal photography-derived aging biomarkers for predicting cognitive d...

SBERO: Skill Al-Biruni Earth Radius Optimization for Alzheimer's Disease Classification Using Magnetic Resonance Image.

Alzheimer's disease (AD) is the most prevalent form of dementia, characterized by progressive memory...

Deep learning-based cell-specific gene regulatory networks inferred from single-cell multiome data.

Gene regulatory networks (GRNs) provide a global representation of how genetic/genomic information i...

[Classification of Alzheimer's disease based on multi-example learning and multi-scale feature fusion].

Alzheimer's disease (AD) classification models usually segment the entire brain image into voxel blo...

Diagnosis of Alzheimer's disease using FusionNet with improved secretary bird optimization algorithm for optimal MK-SVM based on imaging genetic data.

Alzheimer's disease is an irreversible central neurodegenerative disease, and early diagnosis of Alz...

Machine learning prediction of tau-PET in Alzheimer's disease using plasma, MRI, and clinical data.

INTRODUCTION: Tau positron emission tomography (PET) is a reliable neuroimaging technique for assess...

Sleep efficiency in community-dwelling persons living with dementia: exploratory analysis using machine learning.

STUDY OBJECTIVES: Sleep disturbances lead to negative health outcomes and caregiver burden, particul...

Analysis of TEM micrographs with deep learning reveals APOE genotype-specific associations between HDL particle diameter and Alzheimer's dementia.

High-density lipoprotein (HDL) particle diameter distribution is informative in the diagnosis of man...

COX-2 Inhibitor Prediction With KNIME: A Codeless Automated Machine Learning-Based Virtual Screening Workflow.

Cyclooxygenase-2 (COX-2) is an enzyme that plays a crucial role in inflammation by converting arachi...

Identification of CXCR4 inhibitory activity in natural compounds using cheminformatics-guided machine learning algorithms.

Neurodegenerative disorders are characterised by progressive damage to neurons that leads to cogniti...

Nanocarrier-based targeted drug delivery for Alzheimer's disease: addressing neuroinflammation and enhancing clinical translation.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decl...

Identification and validation of pyroptosis-related genes in Alzheimer's disease based on multi-transcriptome and machine learning.

BACKGROUND: Alzheimer's disease (AD) progression is characterized by persistent neuroinflammation, w...

Leveraging transformers and explainable AI for Alzheimer's disease interpretability.

Alzheimer's disease (AD) is a progressive brain ailment that causes memory loss, cognitive decline, ...

Artificial intelligence and omics-based autoantibody profiling in dementia.

INTRODUCTION: Dementia is a neurodegenerative syndrome marked by the accumulation of disease-specifi...

Comprehensive Machine Learning-Based Prediction Model for Delirium Risk in Older Patients with Dementia: Risk Factors Identification.

BACKGROUND: Delirium superimposed on dementia (DSD) is a severe complication in older adults with de...

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