Diagnostic power of resting‐state fMRI for detection of network connectivity in Alzheimer's disease and mild cognitive impairment: A systematic review
Resting‐state fMRI (rs‐fMRI) detects functional connectivity (FC) abnormalities that occur in
the brains of patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI). FC …
the brains of patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI). FC …
Artificial intelligence for diagnostic and prognostic neuroimaging in dementia: A systematic review
Introduction Artificial intelligence (AI) and neuroimaging offer new opportunities for
diagnosis and prognosis of dementia. Methods We systematically reviewed studies …
diagnosis and prognosis of dementia. Methods We systematically reviewed studies …
Four distinct subtypes of Alzheimer's disease based on resting-state connectivity biomarkers
Background Alzheimer's disease (AD) is a neurodegenerative disorder with significant
heterogeneity. Different AD phenotypes may be associated with specific brain network …
heterogeneity. Different AD phenotypes may be associated with specific brain network …
Multimodal representations learning and adversarial hypergraph fusion for early Alzheimer's disease prediction
Multimodal neuroimage can provide complementary information about the dementia, but
small size of complete multimodal data limits the ability in representation learning. Moreover …
small size of complete multimodal data limits the ability in representation learning. Moreover …
Machine learning for detecting parkinson's disease by resting-state functional magnetic resonance imaging: A multicenter radiomics analysis
Parkinson's disease (PD) is one of the most common progressive degenerative diseases,
and its diagnosis is challenging on clinical grounds. Clinically, effective and quantifiable …
and its diagnosis is challenging on clinical grounds. Clinically, effective and quantifiable …
Community graph convolution neural network for alzheimer's disease classification and pathogenetic factors identification
XA Bi, K Chen, S Jiang, S Luo, W Zhou… - … on Neural Networks …, 2023 - ieeexplore.ieee.org
As a complex neural network system, the brain regions and genes collaborate to effectively
store and transmit information. We abstract the collaboration correlations as the brain region …
store and transmit information. We abstract the collaboration correlations as the brain region …
Hypergraph convolutional network for longitudinal data analysis in Alzheimer's disease
Alzheimer's disease (AD) is an irreversible and progressive neurodegenerative disease.
Longitudinal structural magnetic resonance imaging (sMRI) data have been widely used for …
Longitudinal structural magnetic resonance imaging (sMRI) data have been widely used for …
Structural and functional connectivity abnormalities of the default mode network in patients with Alzheimer's disease and mild cognitive impairment within two …
B Zhou, X Dou, W Wang, H Yao, F Feng, P Wang… - Methods, 2022 - Elsevier
Alzheimer's disease (AD) is a chronic neurodegenerative disease characterized by
progressive dementia, and amnestic mild cognitive impairment (aMCI) has been defined as …
progressive dementia, and amnestic mild cognitive impairment (aMCI) has been defined as …
Regional radiomics similarity networks (R2SNs) in the human brain: reproducibility, small-world properties and a biological basis
A structural covariance network (SCN) has been used successfully in structural magnetic
resonance imaging (sMRI) studies. However, most SCNs have been constructed by a …
resonance imaging (sMRI) studies. However, most SCNs have been constructed by a …
Machine learning of schizophrenia detection with structural and functional neuroimaging
Schizophrenia (SZ) is a severe psychiatric illness, and it affects around 1% of the general
population; however, its reliable diagnosis is challenging. Functional MRI (fMRI) and …
population; however, its reliable diagnosis is challenging. Functional MRI (fMRI) and …