Benchmarking functional connectome-based predictive models for resting-state fMRI
Functional connectomes reveal biomarkers of individual psychological or clinical traits.
However, there is great variability in the analytic pipelines typically used to derive them from …
However, there is great variability in the analytic pipelines typically used to derive them from …
Resting state fMRI functional connectivity-based classification using a convolutional neural network architecture
Machine learning techniques have become increasingly popular in the field of resting state
fMRI (functional magnetic resonance imaging) network based classification. However, the …
fMRI (functional magnetic resonance imaging) network based classification. However, the …
Resting state fMRI functional connectivity analysis using dynamic time warping
Traditional resting-state network concept is based on calculating linear dependence of
spontaneous low frequency fluctuations of the BOLD signals of different brain areas, which …
spontaneous low frequency fluctuations of the BOLD signals of different brain areas, which …
Feature selection with a genetic algorithm for classification of brain imaging data
Recent advances in brain imaging technology, coupled with large-scale brain research
projects, such as the BRAIN initiative in the US and the European Human Brain Project …
projects, such as the BRAIN initiative in the US and the European Human Brain Project …
A novel CNN framework to extract multi-level modular features for the classification of brain networks
J Ji, Y Yao - Applied Intelligence, 2022 - Springer
Brain disease diagnosis based on brain network classification has become a hot topic.
Recently, classification methods based on convolutional neural networks (CNNs) have …
Recently, classification methods based on convolutional neural networks (CNNs) have …
Visual Representation and Layout Optimization for Comparison of Dynamic Graph
L Zhang, X Wang, Y Liu, G Zhang… - 2022 IEEE Smartworld …, 2022 - ieeexplore.ieee.org
The comparison between temporal graph data and the representation of the results are very
helpful for in-depth understanding of the difference between the two data. However, limited …
helpful for in-depth understanding of the difference between the two data. However, limited …
A compound classification model for schizophrenia based on brain fmri and network modelling
P Liu, X Mei, S Fei - 2019 Chinese control conference (CCC), 2019 - ieeexplore.ieee.org
Identifying of Schizophrenia patients' fMRI data has attracted lots of researchers' attention.
Due to the complex nature of fMRI data, we need to generate “networks” to analyze the …
Due to the complex nature of fMRI data, we need to generate “networks” to analyze the …
New approaches for fMRI functional connectivity analysis based on Dynamic Time Warping and machine learning
RJ Meszlényi - 2017 - search.proquest.com
Over the last decade resting state functional magnetic resonance imaging (fMRI)(Biswal et
al., 1995, 2010) became a well-known and frequently applied method in functional …
al., 1995, 2010) became a well-known and frequently applied method in functional …