AIMC Topic: Alzheimer Disease

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[An ensemble model for assisting early Alzheimer's disease diagnosis based on structural magnetic resonance imaging with dual-time-point fusion].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Alzheimer's Disease (AD) is a progressive neurodegenerative disorder. Due to the subtlety of symptoms in the early stages of AD, rapid and accurate clinical diagnosis is challenging, leading to a high rate of misdiagnosis. Current research on early d...

AmyloidPETNet: Classification of Amyloid Positivity in Brain PET Imaging Using End-to-End Deep Learning.

Radiology
Background Visual assessment of amyloid PET scans relies on the availability of radiologist expertise, whereas quantification of amyloid burden typically involves MRI for processing and analysis, which can be computationally expensive. Purpose To dev...

Disease-driven domain generalization for neuroimaging-based assessment of Alzheimer's disease.

Human brain mapping
Development of deep learning models to evaluate structural brain changes caused by cognitive impairment in MRI scans holds significant translational value. The efficacy of these models often encounters challenges due to variabilities arising from dif...

AITeQ: a machine learning framework for Alzheimer's prediction using a distinctive five-gene signature.

Briefings in bioinformatics
Neurodegenerative diseases, such as Alzheimer's disease, pose a significant global health challenge with their complex etiology and elusive biomarkers. In this study, we developed the Alzheimer's Identification Tool (AITeQ) using ribonucleic acid-seq...

[A study of cognitive impairment quantitative assessment method based on gait characteristics].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Alzheimer's disease (AD) is a common and serious form of elderly dementia, but early detection and treatment of mild cognitive impairment can help slow down the progression of dementia. Recent studies have shown that there is a relationship between o...

Exploration of Imaging Genetic Biomarkers of Alzheimer's Disease Based on a Machine Learning Method.

Journal of integrative neuroscience
BACKGROUND: Alzheimer's disease (AD) is an irreversible primary brain disease with insidious onset. The rise of imaging genetics research has led numerous researchers to examine the complex association between genes and brain phenotypes from the pers...

Deep Learning and Machine Learning Algorithms for Retinal Image Analysis in Neurodegenerative Disease: Systematic Review of Datasets and Models.

Translational vision science & technology
PURPOSE: Retinal images contain rich biomarker information for neurodegenerative disease. Recently, deep learning models have been used for automated neurodegenerative disease diagnosis and risk prediction using retinal images with good results.

scGraph2Vec: a deep generative model for gene embedding augmented by graph neural network and single-cell omics data.

GigaScience
BACKGROUND: Exploring the cellular processes of genes from the aspects of biological networks is of great interest to understanding the properties of complex diseases and biological systems. Biological networks, such as protein-protein interaction ne...

An Interpretable Population Graph Network to Identify Rapid Progression of Alzheimer's Disease Using UK Biobank.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Alzheimer's disease (AD) manifests with varying progression rates across individuals, necessitating the understanding of their intricate patterns of cognition decline that could contribute to effective strategies for risk monitoring. In this study, w...

Ensuring Fairness in Detecting Mild Cognitive Impairment with MRI.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Machine learning (ML) algorithms play a crucial role in the early and accurate diagnosis of Alzheimer's Disease (AD), which is essential for effective treatment planning. However, existing methods are not well-suited for identifying Mild Cognitive Im...