Manuscripts on this dataset

1. 

   CMS Manager @ 11:48 pm on 26 Dec 2023

   Manuscripts on this dataset, "ds003478"

2. 

   CMS Manager @ 6:07 pm on 12 Feb 2024

   1. CP Da Silva, S Tedesco, B O'Flynn, EEG datasets for healthcare: a scoping review, IEEE Access, 2024, Cited by 0, https://ieeexplore.ieee.org/abstract/document/10466559/
   2. J Chang, Y Choi, Depression diagnosis based on electroencephalography power ratios, Brain and Behavior, 2023, Cited by 0, https://onlinelibrary.wiley.com/doi/abs/10.1002/brb3.3173
   3. G Luo, P An, Y Li, R Hong, S Chen, Exploring adaptive graph topologies and temporal graph networks for eeg-based depression detection, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2023, Cited by 2, https://ieeexplore.ieee.org/abstract/document/10268256/
   4. D Sihn, JS Kim, OS Kwon, SP Kim, Breakdown of long-range spatial correlations of infraslow amplitude fluctuations of EEG oscillations in patients with current and past major depressive …, Frontiers in Psychiatry, 2023, Cited by 2, https://www.frontiersin.org/journals/psychiatry/articles/10.3389/fpsyt.2023.1132996/full
   5. N Shusharina, D Yukhnenko, S Botman, V Sapunov, Modern methods of diagnostics and treatment of neurodegenerative diseases and depression, Diagnostics, 2023, Cited by 15, https://www.mdpi.com/2075-4418/13/3/573
   6. N Draudt, BATS: Development of a Biosignal Analysis Toolkit and Pipeline for Polytrauma Research, 2022, Cited by 0, https://digital.wpi.edu/downloads/5t34sp28g
   7. NP Tigga, S Garg, Efficacy of novel attention-based gated recurrent units transformer for depression detection using electroencephalogram signals, Health Information Science and Systems, 2022, Cited by 8, https://link.springer.com/article/10.1007/s13755-022-00205-8
   8. C Hung, The Impact of Cross-Validation on the Automated EEG-Based Diagnosis, 2022, Cited by 0, http://arno.uvt.nl/show.cgi?fid=160995
   9. V Savinov, V Sapunov, N Shusharina, Research and selection of the optimal neural network architecture and parameters for depression classification using harmonized datasets, 2022 Fourth International Conference Neurotechnologies and Neurointerfaces (CNN), 2022, Cited by 1, https://ieeexplore.ieee.org/abstract/document/9912567/
   10. L Minkowski, CLASSIFYING SEVERITY OF DEPRESSION AND ANXIETY BY ANALYZING ELECTROENCEPHALOGRAPHY (EEG) SIGNALS FOR NEUROPHYSIOLOGICAL …, 2021, Cited by 0, https://rshare.library.torontomu.ca/articles/thesis/Classifying_Severity_of_Depression_and_Anxiety_by_Analyzing_Electroencephalography_EEG_Signals_for_Neurophysiological_Biomarkers/24625206/1/files/43269018.pdf
   11. V Savinov, V Sapunov, N Shusharina, EEG-based depression classification using harmonized datasets, 2021 Third International Conference Neurotechnologies and Neurointerfaces (CNN), 2021, Cited by 4, https://ieeexplore.ieee.org/abstract/document/9580293/

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