124 related articles for article (PubMed ID: 38187601)
1. Evaluating Augmentation Approaches for Deep Learning-based Major Depressive Disorder Diagnosis with Raw Electroencephalogram Data.
Ellis CA; Miller RL; Calhoun VD
bioRxiv; 2023 Dec; ():. PubMed ID: 38187601
[TBL] [Abstract][Full Text] [Related]
2. Improving Multichannel Raw Electroencephalography-based Diagnosis of Major Depressive Disorder via Transfer Learning with Single Channel Sleep Stage Data.
Ellis CA; Sattiraju A; Miller RL; Calhoun VD
bioRxiv; 2023 Oct; ():. PubMed ID: 37873255
[TBL] [Abstract][Full Text] [Related]
3. Improving Multichannel Raw Electroencephalography-based Diagnosis of Major Depressive Disorder by Pretraining Deep Learning Models with Single Channel Sleep Stage Data.
Ellis CA; Sattiraju A; Miller RL; Calhoun VD
bioRxiv; 2023 May; ():. PubMed ID: 37398050
[TBL] [Abstract][Full Text] [Related]
4. Identifying EEG Biomarkers of Depression with Novel Explainable Deep Learning Architectures.
Ellis CA; Sancho ML; Miller RL; Calhoun VD
bioRxiv; 2024 Mar; ():. PubMed ID: 38562835
[TBL] [Abstract][Full Text] [Related]
5. CROSS-SAMPLING RATE TRANSFER LEARNING FOR ENHANCED RAW EEG DEEP LEARNING CLASSIFIER PERFORMANCE IN MAJOR DEPRESSIVE DISORDER DIAGNOSIS.
Ellis CA; Miller RL; Calhoun VD
bioRxiv; 2023 Nov; ():. PubMed ID: 38014293
[TBL] [Abstract][Full Text] [Related]
6. An Explainable and Robust Deep Learning Approach for Automated Electroencephalography-based Schizophrenia Diagnosis.
Sattiraju A; Ellis CA; Miller RL; Calhoun VD
bioRxiv; 2023 Oct; ():. PubMed ID: 37398173
[TBL] [Abstract][Full Text] [Related]
7. NOVEL APPROACH EXPLAINS SPATIO-SPECTRAL INTERACTIONS IN RAW ELECTROENCEPHALOGRAM DEEP LEARNING CLASSIFIERS.
Ellis CA; Sattiraju A; Miller RL; Calhoun VD
bioRxiv; 2023 Feb; ():. PubMed ID: 36909628
[TBL] [Abstract][Full Text] [Related]
8. Data augmentation for deep-learning-based electroencephalography.
Lashgari E; Liang D; Maoz U
J Neurosci Methods; 2020 Dec; 346():108885. PubMed ID: 32745492
[TBL] [Abstract][Full Text] [Related]
9. Identifying Reproducibly Important EEG Markers of Schizophrenia with an Explainable Multi-Model Deep Learning Approach.
Sancho ML; Ellis CA; Miller RL; Calhoun VD
bioRxiv; 2024 Feb; ():. PubMed ID: 38405889
[TBL] [Abstract][Full Text] [Related]
10. Data Augmentation: Using Channel-Level Recombination to Improve Classification Performance for Motor Imagery EEG.
Pei Y; Luo Z; Yan Y; Yan H; Jiang J; Li W; Xie L; Yin E
Front Hum Neurosci; 2021; 15():645952. PubMed ID: 33776673
[TBL] [Abstract][Full Text] [Related]
11. Data augmentation for enhancing EEG-based emotion recognition with deep generative models.
Luo Y; Zhu LZ; Wan ZY; Lu BL
J Neural Eng; 2020 Oct; 17(5):056021. PubMed ID: 33052888
[TBL] [Abstract][Full Text] [Related]
12. Generation of synthetic EEG data for training algorithms supporting the diagnosis of major depressive disorder.
Carrle FP; Hollenbenders Y; Reichenbach A
Front Neurosci; 2023; 17():1219133. PubMed ID: 37849893
[TBL] [Abstract][Full Text] [Related]
13. DiffMDD: A Diffusion-Based Deep Learning Framework for MDD Diagnosis Using EEG.
Wang Y; Zhao S; Jiang H; Li S; Luo B; Li T; Pan G
IEEE Trans Neural Syst Rehabil Eng; 2024; 32():728-738. PubMed ID: 38294930
[TBL] [Abstract][Full Text] [Related]
14. A Survey on Deep Learning-Based Short/Zero-Calibration Approaches for EEG-Based Brain-Computer Interfaces.
Ko W; Jeon E; Jeong S; Phyo J; Suk HI
Front Hum Neurosci; 2021; 15():643386. PubMed ID: 34140883
[TBL] [Abstract][Full Text] [Related]
15. Predicting treatment response using EEG in major depressive disorder: A machine-learning meta-analysis.
Watts D; Pulice RF; Reilly J; Brunoni AR; Kapczinski F; Passos IC
Transl Psychiatry; 2022 Aug; 12(1):332. PubMed ID: 35961967
[TBL] [Abstract][Full Text] [Related]
16. Deep convolutional neural network and IoT technology for healthcare.
Wassan S; Dongyan H; Suhail B; Jhanjhi NZ; Xiao G; Ahmed S; Murugesan RK
Digit Health; 2024; 10():20552076231220123. PubMed ID: 38250147
[TBL] [Abstract][Full Text] [Related]
17. A review of medical image data augmentation techniques for deep learning applications.
Chlap P; Min H; Vandenberg N; Dowling J; Holloway L; Haworth A
J Med Imaging Radiat Oncol; 2021 Aug; 65(5):545-563. PubMed ID: 34145766
[TBL] [Abstract][Full Text] [Related]
18. An end-to-end CNN with attentional mechanism applied to raw EEG in a BCI classification task.
Lashgari E; Ott J; Connelly A; Baldi P; Maoz U
J Neural Eng; 2021 Aug; 18(4):. PubMed ID: 34352734
[No Abstract] [Full Text] [Related]
19. TinySleepNet: An Efficient Deep Learning Model for Sleep Stage Scoring based on Raw Single-Channel EEG.
Supratak A; Guo Y
Annu Int Conf IEEE Eng Med Biol Soc; 2020 Jul; 2020():641-644. PubMed ID: 33018069
[TBL] [Abstract][Full Text] [Related]
20. Depressive Disorder Recognition Based on Frontal EEG Signals and Deep Learning.
Xu Y; Zhong H; Ying S; Liu W; Chen G; Luo X; Li G
Sensors (Basel); 2023 Oct; 23(20):. PubMed ID: 37896732
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
