Classification and prediction of brain disorders using functional connectivity: promising but challenging
Brain functional imaging data, especially functional magnetic resonance imaging (fMRI)
data, have been employed to reflect functional integration of the brain. Alteration in brain …
data, have been employed to reflect functional integration of the brain. Alteration in brain …
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 …
Multi-scale enhanced graph convolutional network for mild cognitive impairment detection
As an early stage of Alzheimer's disease (AD), mild cognitive impairment (MCI) is able to be
detected by analyzing the brain connectivity networks. For this reason, we devise a new …
detected by analyzing the brain connectivity networks. For this reason, we devise a new …
Multicenter and multichannel pooling GCN for early AD diagnosis based on dual-modality fused brain network
For significant memory concern (SMC) and mild cognitive impairment (MCI), their
classification performance is limited by confounding features, diverse imaging protocols, and …
classification performance is limited by confounding features, diverse imaging protocols, and …
Graph convolution network with similarity awareness and adaptive calibration for disease-induced deterioration prediction
Graph convolution networks (GCN) have been successfully applied in disease prediction
tasks as they capture interactions (ie, edges and edge weights on the graph) between …
tasks as they capture interactions (ie, edges and edge weights on the graph) between …
Extraction of dynamic functional connectivity from brain grey matter and white matter for MCI classification
Brain functional connectivity (FC) extracted from resting‐state fMRI (RS‐fMRI) has become a
popular approach for diagnosing various neurodegenerative diseases, including …
popular approach for diagnosing various neurodegenerative diseases, including …
Deep spatial-temporal feature fusion from adaptive dynamic functional connectivity for MCI identification
Dynamic functional connectivity (dFC) analysis using resting-state functional Magnetic
Resonance Imaging (rs-fMRI) is currently an advanced technique for capturing the dynamic …
Resonance Imaging (rs-fMRI) is currently an advanced technique for capturing the dynamic …
Strength and similarity guided group-level brain functional network construction for MCI diagnosis
Sparse representation-based brain functional network modeling often results in large inter-
subject variability in the network structure. This could reduce the statistical power in group …
subject variability in the network structure. This could reduce the statistical power in group …
Multiple measurement analysis of resting-state fMRI for ADHD classification in adolescent brain from the ABCD study
Z Wang, X Zhou, Y Gui, M Liu, H Lu - Translational Psychiatry, 2023 - nature.com
Attention deficit hyperactivity disorder (ADHD) is one of the most common psychiatric
disorders in school-aged children. Its accurate diagnosis looks after patients' interests well …
disorders in school-aged children. Its accurate diagnosis looks after patients' interests well …
Brainnet: Epileptic wave detection from seeg with hierarchical graph diffusion learning
Epilepsy is one of the most serious neurological diseases, affecting 1-2% of the world's
population. The diagnosis of epilepsy depends heavily on the recognition of epileptic waves …
population. The diagnosis of epilepsy depends heavily on the recognition of epileptic waves …