AIMC Topic: Alzheimer Disease

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Quantitative Longitudinal Predictions of Alzheimer's Disease by Multi-Modal Predictive Learning.

Journal of Alzheimer's disease : JAD Jan 1, 2021
BACKGROUND: Quantitatively predicting the progression of Alzheimer's disease (AD) in an individual on a continuous scale, such as the Alzheimer's Disease Assessment Scale-cognitive (ADAS-cog) scores, is informative for a personalized approach as oppo...
Humans Machine Learning Disease Progression Regression Analysis Alzheimer Disease Multivariate Analysis
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Analysis of Risk Factors in Dementia Through Machine Learning.

Journal of Alzheimer's disease : JAD Jan 1, 2021
BACKGROUND: Sociodemographic data indicate the progressive increase in life expectancy and the prevalence of Alzheimer's disease (AD). AD is raised as one of the greatest public health problems. Its etiology is twofold: on the one hand, non-modifiabl...
Tobacco Use Cognitive Reserve Neurocognitive Disorders Socioeconomic Factors Hypertension Alzheimer Disease Case-Control Studies Depression Diabetes Mellitus, Type 2 Female Risk Factors Humans Aged Machine Learning Male Aged, 80 and over Algorithms Exercise Sensitivity and Specificity
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Machine Learning-Supported Analyses Improve Quantitative Histological Assessments of Amyloid-β Deposits and Activated Microglia.

Journal of Alzheimer's disease : JAD Jan 1, 2021
BACKGROUND: Detailed pathology analysis and morphological quantification is tedious and prone to errors. Automatic image analysis can help to increase objectivity and reduce time. Here, we present the evaluation of the DeePathology STUDIO™ for automa...
Alzheimer Disease Mice, Transgenic Plaque, Amyloid Mice Disease Models, Animal Microglia Machine Learning Animals Image Processing, Computer-Assisted
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Construction of MRI-Based Alzheimer's Disease Score Based on Efficient 3D Convolutional Neural Network: Comprehensive Validation on 7,902 Images from a Multi-Center Dataset.

Journal of Alzheimer's disease : JAD Jan 1, 2021
BACKGROUND: In recent years, many convolutional neural networks (CNN) have been proposed for the classification of Alzheimer's disease. Due to memory constraints, many of the proposed CNNs work at a 2D slice-level or 3D patch-level.
Reproducibility of Results Cognitive Dysfunction Imaging, Three-Dimensional Humans Neural Networks, Computer Brain Magnetic Resonance Imaging Alzheimer Disease
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Diagnosis of Alzheimer's Disease Based on Deeply-Fused Nets.

Combinatorial chemistry & high throughput screening Jan 1, 2021
AIM AND OBJECTIVE: Fast and accurate diagnosis of Alzheimer's disease is very important for the care and further treatment of patients. Along with the development of deep learning, impressive progress has also been made in the automatic diagnosis of ...
Deep Learning Magnetic Resonance Imaging Alzheimer Disease Humans
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DeepDicomSort: An Automatic Sorting Algorithm for Brain Magnetic Resonance Imaging Data.

Neuroinformatics Jan 1, 2021
With the increasing size of datasets used in medical imaging research, the need for automated data curation is arising. One important data curation task is the structured organization of a dataset for preserving integrity and ensuring reusability. Th...
Magnetic Resonance Imaging Alzheimer Disease Neuroimaging Humans Neural Networks, Computer Algorithms Brain Brain Neoplasms Image Processing, Computer-Assisted
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Reproducible Evaluation of Diffusion MRI Features for Automatic Classification of Patients with Alzheimer's Disease.

Neuroinformatics Jan 1, 2021
Diffusion MRI is the modality of choice to study alterations of white matter. In past years, various works have used diffusion MRI for automatic classification of Alzheimer's disease. However, classification performance obtained with different approa...
Humans Machine Learning Brain Male Alzheimer Disease Image Interpretation, Computer-Assisted Diffusion Magnetic Resonance Imaging Female Aged Aged, 80 and over
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A systematic literature review of automatic Alzheimer's disease detection from speech and language.

Journal of the American Medical Informatics Association : JAMIA Nov 1, 2020
OBJECTIVE: In recent years numerous studies have achieved promising results in Alzheimer's Disease (AD) detection using automatic language processing. We systematically review these articles to understand the effectiveness of this approach, identify ...
Alzheimer Disease Language Tests Language Disorders Speech Decision Trees Natural Language Processing Humans Artificial Intelligence Machine Learning
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Binary Classification of Alzheimer's Disease Using sMRI Imaging Modality and Deep Learning.

Journal of digital imaging Oct 1, 2020
Alzheimer's disease (AD) is an irreversible devastative neurodegenerative disorder associated with progressive impairment of memory and cognitive functions. Its early diagnosis is crucial for the development of possible future treatment option(s). St...
Alzheimer Disease Humans Neuroimaging Female Cross-Sectional Studies Male Deep Learning Magnetic Resonance Imaging
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Regularized Bagged Canonical Component Analysis for Multiclass Learning in Brain Imaging.

Neuroinformatics Oct 1, 2020
A fundamental problem of supervised learning algorithms for brain imaging applications is that the number of features far exceeds the number of subjects. In this paper, we propose a combined feature selection and extraction approach for multiclass pr...
Disease Progression Cognitive Dysfunction Aged Pattern Recognition, Automated Humans Child Aged, 80 and over Neuroimaging Machine Learning Attention Deficit Disorder with Hyperactivity Male Brain Magnetic Resonance Imaging Female Alzheimer Disease Image Interpretation, Computer-Assisted
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