AIMC Topic: Alzheimer Disease
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A deep learning framework with an embedded-based feature selection approach for the early detection of the Alzheimer's disease.
Computers in biology and medicine
Nov 22, 2021
Ageing is associated with various ailments including Alzheimer 's disease (AD), which is a progressive form of dementia. AD symptoms develop over a period of years and, unfortunately, there is no cure. Existing AD treatments can only slow down the pr...
Deep learning based pipelines for Alzheimer's disease diagnosis: A comparative study and a novel deep-ensemble method.
Computers in biology and medicine
Nov 21, 2021
BACKGROUND: Alzheimer's disease is a chronic neurodegenerative disease that destroys brain cells, causing irreversible degeneration of cognitive functions and dementia. Its causes are not yet fully understood, and there is no curative treatment. Howe...
Identification of Alzheimer associated differentially expressed gene through microarray data and transfer learning-based image analysis.
Neuroscience letters
Nov 19, 2021
Major factors contribute to mental stress and enhance the progression of late-onset Alzheimer's disease (AD). The factors that lead to neurodegeneration, such as tau protein hyperphosphorylation and increased amyloid-beta production, can be mimicked ...
Effect of data leakage in brain MRI classification using 2D convolutional neural networks.
Scientific reports
Nov 19, 2021
In recent years, 2D convolutional neural networks (CNNs) have been extensively used to diagnose neurological diseases from magnetic resonance imaging (MRI) data due to their potential to discern subtle and intricate patterns. Despite the high perform...
Humans
Neural Networks, Computer
Brain
Image Interpretation, Computer-Assisted
Neuroimaging
Middle Aged
Predictive Value of Tests
Case-Control Studies
Alzheimer Disease
Deep Learning
Magnetic Resonance Imaging
Parkinson Disease
Female
Aged, 80 and over
Reproducibility of Results
Cross-Sectional Studies
Male
Aged
Plasma neurofilament light chain protein is not increased in treatment-resistant schizophrenia and first-degree relatives.
The Australian and New Zealand journal of psychiatry
Nov 17, 2021
OBJECTIVE: Schizophrenia, a complex psychiatric disorder, is often associated with cognitive, neurological and neuroimaging abnormalities. The processes underlying these abnormalities, and whether a subset of people with schizophrenia have a neuropro...
Predictive value of ATN biomarker profiles in estimating disease progression in Alzheimer's disease dementia.
Alzheimer's & dementia : the journal of the Alzheimer's Association
Nov 10, 2021
We aimed to evaluate the value of ATN biomarker classification system (amyloid beta [A], pathologic tau [T], and neurodegeneration [N]) for predicting conversion from mild cognitive impairment (MCI) to dementia. In a sample of people with MCI (n = 41...
Improving Sensitivity of Arterial Spin Labeling Perfusion MRI in Alzheimer's Disease Using Transfer Learning of Deep Learning-Based ASL Denoising.
Journal of magnetic resonance imaging : JMRI
Nov 6, 2021
BACKGROUND: Arterial spin labeling (ASL) perfusion magnetic resonance imaging (MRI) denoising through deep learning (DL) often faces insufficient training data from patients. One solution is to train DL models using healthy subjects' data which are m...
A parallel attention-augmented bilinear network for early magnetic resonance imaging-based diagnosis of Alzheimer's disease.
Human brain mapping
Oct 22, 2021
Structural magnetic resonance imaging (sMRI) can capture the spatial patterns of brain atrophy in Alzheimer's disease (AD) and incipient dementia. Recently, many sMRI-based deep learning methods have been developed for AD diagnosis. Some of these met...
Deep learning reveals disease-specific signatures of white matter pathology in tauopathies.
Acta neuropathologica communications
Oct 21, 2021
Although pathology of tauopathies is characterized by abnormal tau protein aggregation in both gray and white matter regions of the brain, neuropathological investigations have generally focused on abnormalities in the cerebral cortex because the can...
Feasibility evaluation of PET scan-time reduction for diagnosing amyloid-β levels in Alzheimer's disease patients using a deep-learning-based denoising algorithm.
Computers in biology and medicine
Oct 4, 2021
PURPOSE: To shorten positron emission tomography (PET) scanning time in diagnosing amyloid-β levels thus increasing the workflow in centers involving Alzheimer's Disease (AD) patients.
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