Application of deep learning for prediction of alzheimer's disease in PET/MR imaging
Y Zhao, Q Guo, Y Zhang, J Zheng, Y Yang, X Du… - Bioengineering, 2023 - mdpi.com
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that affects millions of
people worldwide. Positron emission tomography/magnetic resonance (PET/MR) imaging is …
people worldwide. Positron emission tomography/magnetic resonance (PET/MR) imaging is …
[HTML][HTML] Assessment of memory deficits in psychiatric disorders: A systematic literature review
A Kushwaha, DS Basera, S Kumari… - … of Neurosciences in …, 2024 - ncbi.nlm.nih.gov
Memory deficits are observed across psychiatric disorders ranging from the prodrome of
psychosis to common mental disorders such as anxiety, depression, and dissociative …
psychosis to common mental disorders such as anxiety, depression, and dissociative …
Deep learning based diagnosis of Alzheimer's disease using FDG-PET images
Purpose The aim of this study is to develop a deep neural network to diagnosis Alzheimer's
disease and categorize the stages of the disease using FDG-PET scans …
disease and categorize the stages of the disease using FDG-PET scans …
18F-FDG-PET-based deep learning for predicting cognitive decline in non-demented elderly across the Alzheimer's disease clinical spectrum
Background With disease-modifying treatments for Alzheimer's disease (AD), prognostic
tools for the pre-dementia stage are needed. This study aimed to evaluate the prognostic …
tools for the pre-dementia stage are needed. This study aimed to evaluate the prognostic …
Modeling Brain Functional Networks Using Graph Neural Networks: A Review and Clinical Application
W Zhang, Q Hong - IECE Transactions on Intelligent Systematics, 2024 - iece.org
The integration of graph neural networks (GNNs) with brain functional network analysis is an
emerging field that combines neuroscience and machine learning to enhance our …
emerging field that combines neuroscience and machine learning to enhance our …
Biomarkers from multi-tracer and multi-modal neuroimaging in age-related neurodegenerative diseases
B Nie - Frontiers in Aging Neuroscience, 2022 - frontiersin.org
With the progress of neuroimaging methods, more neurodegenerative diseases have been
revealed to have heterogeneous phenotypes and stages (Leyton et al., 2011; Thenganatt …
revealed to have heterogeneous phenotypes and stages (Leyton et al., 2011; Thenganatt …