126 related articles for article (PubMed ID: 38562835)
1. 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]
2. 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]
3. 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]
4. 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]
5. 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]
6. A Systematic Approach for Explaining Time and Frequency Features Extracted by Convolutional Neural Networks From Raw Electroencephalography Data.
Ellis CA; Miller RL; Calhoun VD
Front Neuroinform; 2022; 16():872035. PubMed ID: 35712676
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. 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]
9. A Model Visualization-based Approach for Insight into Waveforms and Spectra Learned by CNNs.
Ellis CA; Miller RL; Calhoun VD
Annu Int Conf IEEE Eng Med Biol Soc; 2022 Jul; 2022():1643-1646. PubMed ID: 36086296
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. A Convolutional Autoencoder-based Explainable Clustering Approach for Resting-State EEG Analysis
Ellis CA; Miller RL; Calhoun VD
Annu Int Conf IEEE Eng Med Biol Soc; 2023 Jul; 2023():1-4. PubMed ID: 38083554
[TBL] [Abstract][Full Text] [Related]
12. An explainable deep-learning model to stage sleep states in children and propose novel EEG-related patterns in sleep apnea.
Vaquerizo-Villar F; Gutiérrez-Tobal GC; Calvo E; Álvarez D; Kheirandish-Gozal L; Del Campo F; Gozal D; Hornero R
Comput Biol Med; 2023 Oct; 165():107419. PubMed ID: 37703716
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. Major depressive disorder diagnosis based on effective connectivity in EEG signals: a convolutional neural network and long short-term memory approach.
Saeedi A; Saeedi M; Maghsoudi A; Shalbaf A
Cogn Neurodyn; 2021 Apr; 15(2):239-252. PubMed ID: 33854642
[TBL] [Abstract][Full Text] [Related]
15. Deep Learning of Explainable EEG Patterns as Dynamic Spatiotemporal Clusters and Rules in a Brain-Inspired Spiking Neural Network.
Doborjeh M; Doborjeh Z; Kasabov N; Barati M; Wang GY
Sensors (Basel); 2021 Jul; 21(14):. PubMed ID: 34300640
[TBL] [Abstract][Full Text] [Related]
16. Novel methods for elucidating modality importance in multimodal electrophysiology classifiers.
Ellis CA; Sendi MSE; Zhang R; Carbajal DA; Wang MD; Miller RL; Calhoun VD
Front Neuroinform; 2023; 17():1123376. PubMed ID: 37006636
[TBL] [Abstract][Full Text] [Related]
17. CEFEs: A CNN Explainable Framework for ECG Signals.
Maweu BM; Dakshit S; Shamsuddin R; Prabhakaran B
Artif Intell Med; 2021 May; 115():102059. PubMed ID: 34001319
[TBL] [Abstract][Full Text] [Related]
18. Deep Convolutional Neural Network Applied to Electroencephalography: Raw Data vs Spectral Features.
Truong D; Milham M; Makeig S; Delorme A
Annu Int Conf IEEE Eng Med Biol Soc; 2021 Nov; 2021():1039-1042. PubMed ID: 34891466
[TBL] [Abstract][Full Text] [Related]
19. EEG-based classification of individuals with neuropsychiatric disorders using deep neural networks: A systematic review of current status and future directions.
Parsa M; Rad HY; Vaezi H; Hossein-Zadeh GA; Setarehdan SK; Rostami R; Rostami H; Vahabie AH
Comput Methods Programs Biomed; 2023 Oct; 240():107683. PubMed ID: 37406421
[TBL] [Abstract][Full Text] [Related]
20. Deep learning for electroencephalogram (EEG) classification tasks: a review.
Craik A; He Y; Contreras-Vidal JL
J Neural Eng; 2019 Jun; 16(3):031001. PubMed ID: 30808014
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
