AIMC Topic: Alzheimer Disease

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Cross-Modality Translation with Generative Adversarial Networks to Unveil Alzheimer's Disease Biomarkers.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Generative approaches for cross-modality transformation have recently gained significant attention in neuroimaging. While most previous work has focused on case-control data, the application of generative models to disorder-specific datasets and thei...
Neural Networks, Computer Generative Adversarial Networks Biomarkers Brain Magnetic Resonance Imaging Alzheimer Disease Female Humans Neuroimaging Aged Male
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Dynamic multi-hypergraph structure learning for disease diagnosis on multimodal data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
With its superior capability in complex data modeling, hypergraph computation is a powerful tool for many applications. In this work, we propose using hypergraph computation for disease prediction. Hypergraphs allow for the representation of higher-o...
Humans Neural Networks, Computer Diagnosis, Computer-Assisted Cluster Analysis Alzheimer Disease Machine Learning Algorithms Autism Spectrum Disorder
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Multi-class Prediction of Cognitively Normal / Mild Cognitive Impairment / Alzheimer's Disease Status in Dementia Based on Convolutional Neural Networks with Attention Mechanism.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Alzheimer's disease (AD) is a neurodegenerative disease with insidious onset and progressive development. AD is a health issue that is attracting attention as the world's populations get older. Although there is currently no effective treatment for t...
Cognitive Dysfunction Cognition Magnetic Resonance Imaging Alzheimer Disease Male Deep Learning Humans Convolutional Neural Networks Neural Networks, Computer Female Aged
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Artificial Intelligence Based Hierarchical Classification of Frontotemporal Dementia.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Frontotemporal dementia (FTD) is a typical kind of presenile dementia with three main subtypes: behavioral-variant FTD (bvFTD), non-fluent variant primary progressive aphasia (nfvPPA), and semantic variant primary progressive aphasia (svPPA). Our aim...
Humans Artificial Intelligence Bayes Theorem Discriminant Analysis Alzheimer Disease Female Middle Aged Frontotemporal Dementia Aged Support Vector Machine Neuroimaging Male Magnetic Resonance Imaging
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3D Multi-feature fusion convolutional network for Alzheimer's disease diagnosis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
The cognitive decline caused by Alzheimer's disease (AD) is closely related to the structural changes in the hippocampus captured by structural magnetic resonance imaging (sMRI). However, current deep model research on the morphological analysis of h...
Magnetic Resonance Imaging Alzheimer Disease Hippocampus Male Deep Learning Imaging, Three-Dimensional Algorithms Female Aged Humans Neural Networks, Computer
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Novel Alzheimer's Disease Stating Based on Comorbidities-Informed Graph Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Alzheimer's Disease (AD), the most prevalent form of dementia, requires early prediction for timely intervention. Leveraging data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), our study employs Graph Neural Networks (GNNs) for multi-cl...
Comorbidity Cognitive Dysfunction Alzheimer Disease Female Aged Male Neuroimaging Graph Neural Networks Humans Neural Networks, Computer Algorithms
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Dual Attention Graph Convolutional Network Fusing Imaging and Genetic Data for Early Alzheimer's Disease Diagnosis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Alzheimer's Disease (AD) poses a significant global neurodegenerative challenge, underscoring the urgency of early clinical intervention. Our paper presents a novel approach for early AD diagnosis, focusing on a dual attention graph convolutional net...
Neural Networks, Computer Algorithms Image Processing, Computer-Assisted Alzheimer Disease Humans Early Diagnosis Neuroimaging
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Brain Age Analysis and Dementia Classification using Convolutional Neural Networks trained on Diffusion MRI: Tests in Indian and North American Cohorts.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Deep learning models based on convolutional neural networks (CNNs) have been used to classify Alzheimer's disease or infer dementia severity from T1-weighted brain MRI scans. Here, we examine the value of adding diffusion-weighted MRI (dMRI) as an in...
Aged Male Deep Learning Diffusion Magnetic Resonance Imaging Cohort Studies Neural Networks, Computer India Alzheimer Disease Brain Neuroimaging Convolutional Neural Networks Female Humans North America Dementia
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Graph-based deep learning models in the prediction of early-stage Alzheimers.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Alzheimer's disease is the most common age-related problem and progresses in different stages, from cognitively normal to early mild cognitive impairment, and severe dementia. This study investigates the predictive potential of resting-state function...
Humans Brain Disease Progression Deep Learning Magnetic Resonance Imaging Alzheimer Disease Female Aged Male
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TA-RNN: an attention-based time-aware recurrent neural network architecture for electronic health records.

Bioinformatics (Oxford, England) Jun 28, 2024
MOTIVATION: Electronic health records (EHRs) represent a comprehensive resource of a patient's medical history. EHRs are essential for utilizing advanced technologies such as deep learning (DL), enabling healthcare providers to analyze extensive data...
Deep Learning Humans Alzheimer Disease Neural Networks, Computer Electronic Health Records
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