AIMC Topic: Alzheimer Disease
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[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
Apr 25, 2024
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
Apr 17, 2024
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
Feb 1, 2024
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
Jan 2, 2024
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
Jan 1, 2024
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
Jan 1, 2024
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...
A Study on Machine Learning Models in Detecting Cognitive Impairments in Alzheimer's Patients Using Cerebrospinal Fluid Biomarkers.
American journal of Alzheimer's disease and other dementias
Jan 1, 2024
Several research studies have demonstrated the potential use of cerebrospinal fluid biomarkers such as amyloid beta 1-42, T-tau, and P-tau, in early diagnosis of Alzheimer's disease stages. The levels of these biomarkers in conjunction with the demen...
Towards Explainable Detection of Alzheimer's Disease: A Fusion of Deep Convolutional Neural Network and Enhanced Weighted Fuzzy C-Mean.
Current medical imaging
Jan 1, 2024
BACKGROUND: Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, posing a significant challenge for individuals and society. Early detection and treatment are essential for effective disease managem...
Identifying the Role of Oligodendrocyte Genes in the Diagnosis of Alzheimer's Disease through Machine Learning and Bioinformatics Analysis.
Current Alzheimer research
Jan 1, 2024
BACKGROUND: Due to the heterogeneity of Alzheimer's disease (AD), the underlying pathogenic mechanisms have not been fully elucidated. Oligodendrocyte (OL) damage and myelin degeneration are prevalent features of AD pathology. When oligodendrocytes a...
A Study of Assisted Screening for Alzheimer's Disease Based on Handwriting and Gait Analysis.
Journal of Alzheimer's disease : JAD
Jan 1, 2024
BACKGROUND: Alzheimer's disease (AD) is a progressive neurodegenerative disease that is not easily detected in the early stage. Handwriting and walking have been shown to be potential indicators of cognitive decline and are often affected by AD.
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