AIMC Topic: Alzheimer Disease
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An Exploration: Alzheimer's Disease Classification Based on Convolutional Neural Network.
BioMed research international
Jan 22, 2022
Alzheimer's disease (AD) is the most generally known neurodegenerative disorder, leading to a steady deterioration in cognitive ability. Deep learning models have shown outstanding performance in the diagnosis of AD, and these models do not need any ...
Comparing two artificial intelligence software packages for normative brain volumetry in memory clinic imaging.
Neuroradiology
Jan 15, 2022
PURPOSE: To compare two artificial intelligence software packages performing normative brain volumetry and explore whether they could differently impact dementia diagnostics in a clinical context.
Deep learning for subtyping the Alzheimer's disease spectrum.
Trends in molecular medicine
Jan 4, 2022
In a recent article from Cell Reports Medicine, Kwak et al. generate novel insights about subtyping cognitively impaired individuals based on structural imaging. Quantifying heterogeneity in Alzheimer's disease via subtyping could help us harness new...
Alteration of the corpus callosum in patients with Alzheimer's disease: Deep learning-based assessment.
PloS one
Dec 23, 2021
BACKGROUND: Several studies have reported changes in the corpus callosum (CC) in Alzheimer's disease. However, the involved region differed according to the study population and study group. Using deep learning technology, we ensured accurate analysi...
Deep learning for Alzheimer's disease: Mapping large-scale histological tau protein for neuroimaging biomarker validation.
NeuroImage
Dec 20, 2021
Abnormal tau inclusions are hallmarks of Alzheimer's disease and predictors of clinical decline. Several tau PET tracers are available for neurodegenerative disease research, opening avenues for molecular diagnosis in vivo. However, few have been app...
A whole-process interpretable and multi-modal deep reinforcement learning for diagnosis and analysis of Alzheimer's disease.
Journal of neural engineering
Dec 13, 2021
. Alzheimer's disease (AD), a common disease of the elderly with unknown etiology, has been adversely affecting many people, especially with the aging of the population and the younger trend of this disease. Current artificial intelligence (AI) metho...
Identifying and evaluating clinical subtypes of Alzheimer's disease in care electronic health records using unsupervised machine learning.
BMC medical informatics and decision making
Dec 8, 2021
BACKGROUND: Alzheimer's disease (AD) is a highly heterogeneous disease with diverse trajectories and outcomes observed in clinical populations. Understanding this heterogeneity can enable better treatment, prognosis and disease management. Studies to...
A deep learning framework identifies dimensional representations of Alzheimer's Disease from brain structure.
Nature communications
Dec 3, 2021
Heterogeneity of brain diseases is a challenge for precision diagnosis/prognosis. We describe and validate Smile-GAN (SeMI-supervised cLustEring-Generative Adversarial Network), a semi-supervised deep-clustering method, which examines neuroanatomical...
Use of robots to encourage social engagement between older adults.
Geriatric nursing (New York, N.Y.)
Nov 27, 2021
We designed a robotic architecture system within a commercially available socially assistive robot to engage pairs of older adults in multimodal activities over 3 weeks for 6 sessions. The study took place in two assisted living facilities. Seven pai...
Embracing the disharmony in medical imaging: A Simple and effective framework for domain adaptation.
Medical image analysis
Nov 26, 2021
Domain shift, the mismatch between training and testing data characteristics, causes significant degradation in the predictive performance in multi-source imaging scenarios. In medical imaging, the heterogeneity of population, scanners and acquisitio...
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