988 related articles for article (PubMed ID: 25987366)
1. Deep neural network with weight sparsity control and pre-training extracts hierarchical features and enhances classification performance: Evidence from whole-brain resting-state functional connectivity patterns of schizophrenia.
Kim J; Calhoun VD; Shim E; Lee JH
Neuroimage; 2016 Jan; 124(Pt A):127-146. PubMed ID: 25987366
[TBL] [Abstract][Full Text] [Related]
2. Task-specific feature extraction and classification of fMRI volumes using a deep neural network initialized with a deep belief network: Evaluation using sensorimotor tasks.
Jang H; Plis SM; Calhoun VD; Lee JH
Neuroimage; 2017 Jan; 145(Pt B):314-328. PubMed ID: 27079534
[TBL] [Abstract][Full Text] [Related]
3. Diagnosing Autism Spectrum Disorder from Brain Resting-State Functional Connectivity Patterns Using a Deep Neural Network with a Novel Feature Selection Method.
Guo X; Dominick KC; Minai AA; Li H; Erickson CA; Lu LJ
Front Neurosci; 2017; 11():460. PubMed ID: 28871217
[TBL] [Abstract][Full Text] [Related]
4. Autoencoder and restricted Boltzmann machine for transfer learning in functional magnetic resonance imaging task classification.
Hwang J; Lustig N; Jung M; Lee JH
Heliyon; 2023 Jul; 9(7):e18086. PubMed ID: 37519689
[TBL] [Abstract][Full Text] [Related]
5. Sparse deep neural networks on imaging genetics for schizophrenia case-control classification.
Chen J; Li X; Calhoun VD; Turner JA; van Erp TGM; Wang L; Andreassen OA; Agartz I; Westlye LT; Jönsson E; Ford JM; Mathalon DH; Macciardi F; O'Leary DS; Liu J; Ji S
Hum Brain Mapp; 2021 Jun; 42(8):2556-2568. PubMed ID: 33724588
[TBL] [Abstract][Full Text] [Related]
6. Sparsity-guided multiple functional connectivity patterns for classification of schizophrenia via convolutional network.
Yu R; Pan C; Bian L; Fei X; Chen M; Shen D
Hum Brain Mapp; 2023 Aug; 44(12):4523-4534. PubMed ID: 37318814
[TBL] [Abstract][Full Text] [Related]
7. Deep neural network predicts emotional responses of the human brain from functional magnetic resonance imaging.
Kim HC; Bandettini PA; Lee JH
Neuroimage; 2019 Feb; 186():607-627. PubMed ID: 30366076
[TBL] [Abstract][Full Text] [Related]
8. A Multi-Domain Connectome Convolutional Neural Network for Identifying Schizophrenia From EEG Connectivity Patterns.
Phang CR; Noman F; Hussain H; Ting CM; Ombao H
IEEE J Biomed Health Inform; 2020 May; 24(5):1333-1343. PubMed ID: 31536026
[TBL] [Abstract][Full Text] [Related]
9. Discriminative analysis of resting-state functional connectivity patterns of schizophrenia using low dimensional embedding of fMRI.
Shen H; Wang L; Liu Y; Hu D
Neuroimage; 2010 Feb; 49(4):3110-21. PubMed ID: 19931396
[TBL] [Abstract][Full Text] [Related]
10. Characterizing dynamic amplitude of low-frequency fluctuation and its relationship with dynamic functional connectivity: An application to schizophrenia.
Fu Z; Tu Y; Di X; Du Y; Pearlson GD; Turner JA; Biswal BB; Zhang Z; Calhoun VD
Neuroimage; 2018 Oct; 180(Pt B):619-631. PubMed ID: 28939432
[TBL] [Abstract][Full Text] [Related]
11. fMRI volume classification using a 3D convolutional neural network robust to shifted and scaled neuronal activations.
Vu H; Kim HC; Jung M; Lee JH
Neuroimage; 2020 Dec; 223():117328. PubMed ID: 32896633
[TBL] [Abstract][Full Text] [Related]
12. An attention-based hybrid deep learning framework integrating brain connectivity and activity of resting-state functional MRI data.
Zhao M; Yan W; Luo N; Zhi D; Fu Z; Du Y; Yu S; Jiang T; Calhoun VD; Sui J
Med Image Anal; 2022 May; 78():102413. PubMed ID: 35305447
[TBL] [Abstract][Full Text] [Related]
13. Identifying commonality and specificity across psychosis sub-groups via classification based on features from dynamic connectivity analysis.
Du Y; Hao H; Wang S; Pearlson GD; Calhoun VD
Neuroimage Clin; 2020; 27():102284. PubMed ID: 32563920
[TBL] [Abstract][Full Text] [Related]
14. Enhancing the representation of functional connectivity networks by fusing multi-view information for autism spectrum disorder diagnosis.
Huang H; Liu X; Jin Y; Lee SW; Wee CY; Shen D
Hum Brain Mapp; 2019 Feb; 40(3):833-854. PubMed ID: 30357998
[TBL] [Abstract][Full Text] [Related]
15. Discrimination of schizophrenia auditory hallucinators by machine learning of resting-state functional MRI.
Chyzhyk D; Graña M; Öngür D; Shinn AK
Int J Neural Syst; 2015 May; 25(3):1550007. PubMed ID: 25753600
[TBL] [Abstract][Full Text] [Related]
16. Dynamic functional connectivity in schizophrenia and autism spectrum disorder: Convergence, divergence and classification.
Rabany L; Brocke S; Calhoun VD; Pittman B; Corbera S; Wexler BE; Bell MD; Pelphrey K; Pearlson GD; Assaf M
Neuroimage Clin; 2019; 24():101966. PubMed ID: 31401405
[TBL] [Abstract][Full Text] [Related]
17. A Novel Transfer Learning Approach to Enhance Deep Neural Network Classification of Brain Functional Connectomes.
Li H; Parikh NA; He L
Front Neurosci; 2018; 12():491. PubMed ID: 30087587
[TBL] [Abstract][Full Text] [Related]
18. Identifying functional network changing patterns in individuals at clinical high-risk for psychosis and patients with early illness schizophrenia: A group ICA study.
Du Y; Fryer SL; Lin D; Sui J; Yu Q; Chen J; Stuart B; Loewy RL; Calhoun VD; Mathalon DH
Neuroimage Clin; 2018; 17():335-346. PubMed ID: 29159045
[TBL] [Abstract][Full Text] [Related]
19. A framework for linking resting-state chronnectome/genome features in schizophrenia: A pilot study.
Rashid B; Chen J; Rashid I; Damaraju E; Liu J; Miller R; Agcaoglu O; van Erp TGM; Lim KO; Turner JA; Mathalon DH; Ford JM; Voyvodic J; Mueller BA; Belger A; McEwen S; Potkin SG; Preda A; Bustillo JR; Pearlson GD; Calhoun VD
Neuroimage; 2019 Jan; 184():843-854. PubMed ID: 30300752
[TBL] [Abstract][Full Text] [Related]
20. Aberrant Dynamic Functional Connectivity of Default Mode Network in Schizophrenia and Links to Symptom Severity.
Sendi MSE; Zendehrouh E; Ellis CA; Liang Z; Fu Z; Mathalon DH; Ford JM; Preda A; van Erp TGM; Miller RL; Pearlson GD; Turner JA; Calhoun VD
Front Neural Circuits; 2021; 15():649417. PubMed ID: 33815070
[No Abstract] [Full Text] [Related]
[Next] [New Search]
