829 related articles for article (PubMed ID: 31536026)
1. 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]
2. Detection of schizophrenia using hybrid of deep learning and brain effective connectivity image from electroencephalogram signal.
Bagherzadeh S; Shahabi MS; Shalbaf A
Comput Biol Med; 2022 Jul; 146():105570. PubMed ID: 35504218
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. SchizoNET: a robust and accurate Margenau-Hill time-frequency distribution based deep neural network model for schizophrenia detection using EEG signals.
Khare SK; Bajaj V; Acharya UR
Physiol Meas; 2023 Mar; 44(3):. PubMed ID: 36787641
[No Abstract] [Full Text] [Related]
5. Discriminative analysis of schizophrenia patients using an integrated model combining 3D CNN with 2D CNN: A multimodal MR image and connectomics analysis.
Guo H; Jian S; Zhou Y; Chen X; Chen J; Zhou J; Huang Y; Ma G; Li X; Ning Y; Wu F; Wu K
Brain Res Bull; 2024 Jan; 206():110846. PubMed ID: 38104672
[TBL] [Abstract][Full Text] [Related]
6. Transfer learning with deep convolutional neural network for automated detection of schizophrenia from EEG signals.
Shalbaf A; Bagherzadeh S; Maghsoudi A
Phys Eng Sci Med; 2020 Dec; 43(4):1229-1239. PubMed ID: 32926393
[TBL] [Abstract][Full Text] [Related]
7. Emotional EEG classification using connectivity features and convolutional neural networks.
Moon SE; Chen CJ; Hsieh CJ; Wang JL; Lee JS
Neural Netw; 2020 Dec; 132():96-107. PubMed ID: 32861918
[TBL] [Abstract][Full Text] [Related]
8. Orthogonal convolutional neural networks for automatic sleep stage classification based on single-channel EEG.
Zhang J; Yao R; Ge W; Gao J
Comput Methods Programs Biomed; 2020 Jan; 183():105089. PubMed ID: 31586788
[TBL] [Abstract][Full Text] [Related]
9. 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]
10. Automatic seizure detection using three-dimensional CNN based on multi-channel EEG.
Wei X; Zhou L; Chen Z; Zhang L; Zhou Y
BMC Med Inform Decis Mak; 2018 Dec; 18(Suppl 5):111. PubMed ID: 30526571
[TBL] [Abstract][Full Text] [Related]
11. DNN Filter Bank Improves 1-Max Pooling CNN for Single-Channel EEG Automatic Sleep Stage Classification.
Phan H; Andreotti F; Cooray N; Oliver Chen Y; De Vos M
Annu Int Conf IEEE Eng Med Biol Soc; 2018 Jul; 2018():453-456. PubMed ID: 30440432
[TBL] [Abstract][Full Text] [Related]
12. Diagnosis of schizophrenia with functional connectome data: a graph-based convolutional neural network approach.
Oh KH; Oh IS; Tsogt U; Shen J; Kim WS; Liu C; Kang NI; Lee KH; Sui J; Kim SW; Chung YC
BMC Neurosci; 2022 Jan; 23(1):5. PubMed ID: 35038994
[TBL] [Abstract][Full Text] [Related]
13. A deep learning approach in automated detection of schizophrenia using scalogram images of EEG signals.
Aslan Z; Akin M
Phys Eng Sci Med; 2022 Mar; 45(1):83-96. PubMed ID: 34822131
[TBL] [Abstract][Full Text] [Related]
14. Automatic identification of schizophrenia based on EEG signals using dynamic functional connectivity analysis and 3D convolutional neural network.
Shen M; Wen P; Song B; Li Y
Comput Biol Med; 2023 Jun; 160():107022. PubMed ID: 37187135
[TBL] [Abstract][Full Text] [Related]
15. Major Depressive Disorder Classification Based on Different Convolutional Neural Network Models: Deep Learning Approach.
Uyulan C; Ergüzel TT; Unubol H; Cebi M; Sayar GH; Nezhad Asad M; Tarhan N
Clin EEG Neurosci; 2021 Jan; 52(1):38-51. PubMed ID: 32491928
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. Inter-subject transfer learning with an end-to-end deep convolutional neural network for EEG-based BCI.
Fahimi F; Zhang Z; Goh WB; Lee TS; Ang KK; Guan C
J Neural Eng; 2019 Apr; 16(2):026007. PubMed ID: 30524056
[TBL] [Abstract][Full Text] [Related]
18. ConCeptCNN: A novel multi-filter convolutional neural network for the prediction of neurodevelopmental disorders using brain connectome.
Chen M; Li H; Fan H; Dillman JR; Wang H; Altaye M; Zhang B; Parikh NA; He L
Med Phys; 2022 May; 49(5):3171-3184. PubMed ID: 35246986
[TBL] [Abstract][Full Text] [Related]
19. Ensemble learning with 3D convolutional neural networks for functional connectome-based prediction.
Khosla M; Jamison K; Kuceyeski A; Sabuncu MR
Neuroimage; 2019 Oct; 199():651-662. PubMed ID: 31220576
[TBL] [Abstract][Full Text] [Related]
20. Hybrid machine learning method for a connectivity-based epilepsy diagnosis with resting-state EEG.
Rijnders B; Korkmaz EE; Yildirim F
Med Biol Eng Comput; 2022 Jun; 60(6):1675-1689. PubMed ID: 35435566
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]