AIMC Topic: Alzheimer Disease
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Deep learning detection of informative features in tau PET for Alzheimer's disease classification.
BMC bioinformatics
Dec 28, 2020
BACKGROUND: Alzheimer's disease (AD) is the most common type of dementia, typically characterized by memory loss followed by progressive cognitive decline and functional impairment. Many clinical trials of potential therapies for AD have failed, and ...
Fused Sparse Network Learning for Longitudinal Analysis of Mild Cognitive Impairment.
IEEE transactions on cybernetics
Dec 22, 2020
Alzheimer's disease (AD) is a neurodegenerative disease with an irreversible and progressive process. To understand the brain functions and identify the biomarkers of AD and early stages of the disease [also known as, mild cognitive impairment (MCI)]...
Identification of Alzheimer's disease using a convolutional neural network model based on T1-weighted magnetic resonance imaging.
Scientific reports
Dec 17, 2020
The classification of Alzheimer's disease (AD) using deep learning methods has shown promising results, but successful application in clinical settings requires a combination of high accuracy, short processing time, and generalizability to various po...
EEG-Based Emotion Classification for Alzheimer's Disease Patients Using Conventional Machine Learning and Recurrent Neural Network Models.
Sensors (Basel, Switzerland)
Dec 16, 2020
As the number of patients with Alzheimer's disease (AD) increases, the effort needed to care for these patients increases as well. At the same time, advances in information and sensor technologies have reduced caring costs, providing a potential path...
Transfer learning for predicting conversion from mild cognitive impairment to dementia of Alzheimer's type based on a three-dimensional convolutional neural network.
Neurobiology of aging
Dec 13, 2020
Dementia of Alzheimer's type (DAT) is associated with devastating and irreversible cognitive decline. Predicting which patients with mild cognitive impairment (MCI) will progress to DAT is an ongoing challenge in the field. We developed a deep learni...
A comparison of machine learning methods for survival analysis of high-dimensional clinical data for dementia prediction.
Scientific reports
Nov 23, 2020
Data collected from clinical trials and cohort studies, such as dementia studies, are often high-dimensional, censored, heterogeneous and contain missing information, presenting challenges to traditional statistical analysis. There is an urgent need ...
PredAmyl-MLP: Prediction of Amyloid Proteins Using Multilayer Perceptron.
Computational and mathematical methods in medicine
Nov 20, 2020
Amyloid is generally an aggregate of insoluble fibrin; its abnormal deposition is the pathogenic mechanism of various diseases, such as Alzheimer's disease and type II diabetes. Therefore, accurately identifying amyloid is necessary to understand its...
Identification of early mild cognitive impairment using multi-modal data and graph convolutional networks.
BMC bioinformatics
Nov 18, 2020
BACKGROUND: The identification of early mild cognitive impairment (EMCI), which is an early stage of Alzheimer's disease (AD) and is associated with brain structural and functional changes, is still a challenging task. Recent studies show great promi...
Development and Validation of a Deep Learning-Based Automatic Brain Segmentation and Classification Algorithm for Alzheimer Disease Using 3D T1-Weighted Volumetric Images.
AJNR. American journal of neuroradiology
Nov 5, 2020
BACKGROUND AND PURPOSE: Limited evidence has suggested that a deep learning automatic brain segmentation and classification method, based on T1-weighted brain MR images, can predict Alzheimer disease. Our aim was to develop and validate a deep learni...
Alzheimer's diagnosis using deep learning in segmenting and classifying 3D brain MR images.
The International journal of neuroscience
Nov 4, 2020
BACKGROUND AND OBJECTIVES: Dementia is one of the brain diseases with serious symptoms such as memory loss, and thinking problems. According to the World Alzheimer Report 2016, in the world, there are 47 million people having dementia and it can be 1...
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