BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

189 related articles for article (PubMed ID: 36617798)

  • 1. Classification of EEG signals related to real and imagery knee movements using deep learning for brain computer interfaces.
    Lee Y; Lee HJ; Tae KS
    Technol Health Care; 2023; 31(3):933-942. PubMed ID: 36617798
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A 1D CNN for high accuracy classification and transfer learning in motor imagery EEG-based brain-computer interface.
    Mattioli F; Porcaro C; Baldassarre G
    J Neural Eng; 2022 Jan; 18(6):. PubMed ID: 34920443
    [No Abstract]   [Full Text] [Related]  

  • 3. Classification of motor imagery EEG using deep learning increases performance in inefficient BCI users.
    Tibrewal N; Leeuwis N; Alimardani M
    PLoS One; 2022; 17(7):e0268880. PubMed ID: 35867703
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Validating Deep Neural Networks for Online Decoding of Motor Imagery Movements from EEG Signals.
    Tayeb Z; Fedjaev J; Ghaboosi N; Richter C; Everding L; Qu X; Wu Y; Cheng G; Conradt J
    Sensors (Basel); 2019 Jan; 19(1):. PubMed ID: 30626132
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Motor imagery recognition with automatic EEG channel selection and deep learning.
    Zhang H; Zhao X; Wu Z; Sun B; Li T
    J Neural Eng; 2021 Feb; 18(1):. PubMed ID: 33181505
    [No Abstract]   [Full Text] [Related]  

  • 6. 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]  

  • 7. Motor Imagery EEG Classification Using Capsule Networks.
    Ha KW; Jeong JW
    Sensors (Basel); 2019 Jun; 19(13):. PubMed ID: 31252557
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Spatial-Frequency Feature Learning and Classification of Motor Imagery EEG Based on Deep Convolution Neural Network.
    Miao M; Hu W; Yin H; Zhang K
    Comput Math Methods Med; 2020; 2020():1981728. PubMed ID: 32765639
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Classification Algorithm for Electroencephalogram-based Motor Imagery Using Hybrid Neural Network with Spatio-temporal Convolution and Multi-head Attention Mechanism.
    Shi X; Li B; Wang W; Qin Y; Wang H; Wang X
    Neuroscience; 2023 Sep; 527():64-73. PubMed ID: 37517788
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Motor Imagery Classification Using Inter-Task Transfer Learning via a Channel-Wise Variational Autoencoder-Based Convolutional Neural Network.
    Lee DY; Jeong JH; Lee BH; Lee SW
    IEEE Trans Neural Syst Rehabil Eng; 2022; 30():226-237. PubMed ID: 35041605
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Attention-Based DSC-ConvLSTM for Multiclass Motor Imagery Classification.
    Li L; Sun N
    Comput Intell Neurosci; 2022; 2022():8187009. PubMed ID: 35571721
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A review of critical challenges in MI-BCI: From conventional to deep learning methods.
    Khademi Z; Ebrahimi F; Kordy HM
    J Neurosci Methods; 2023 Jan; 383():109736. PubMed ID: 36349568
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Posthoc Interpretability of Neural Responses by Grouping Subject Motor Imagery Skills Using CNN-Based Connectivity.
    Collazos-Huertas DF; Álvarez-Meza AM; Cárdenas-Peña DA; Castaño-Duque GA; Castellanos-Domínguez CG
    Sensors (Basel); 2023 Mar; 23(5):. PubMed ID: 36904950
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Imagined character recognition through EEG signals using deep convolutional neural network.
    Ullah S; Halim Z
    Med Biol Eng Comput; 2021 May; 59(5):1167-1183. PubMed ID: 33945075
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Portable deep-learning decoder for motor imaginary EEG signals based on a novel compact convolutional neural network incorporating spatial-attention mechanism.
    Wu Z; Tang X; Wu J; Huang J; Shen J; Hong H
    Med Biol Eng Comput; 2023 Sep; 61(9):2391-2404. PubMed ID: 37095297
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Unraveling motor imagery brain patterns using explainable artificial intelligence based on Shapley values.
    Pérez-Velasco S; Marcos-Martínez D; Santamaría-Vázquez E; Martínez-Cagigal V; Moreno-Calderón S; Hornero R
    Comput Methods Programs Biomed; 2024 Apr; 246():108048. PubMed ID: 38308997
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Subject adaptation convolutional neural network for EEG-based motor imagery classification.
    Liu S; Zhang J; Wang A; Wu H; Zhao Q; Long J
    J Neural Eng; 2022 Nov; 19(6):. PubMed ID: 36270467
    [No Abstract]   [Full Text] [Related]  

  • 18. A Combined Virtual Electrode-Based ESA and CNN Method for MI-EEG Signal Feature Extraction and Classification.
    Lun X; Zhang Y; Zhu M; Lian Y; Hou Y
    Sensors (Basel); 2023 Nov; 23(21):. PubMed ID: 37960592
    [TBL] [Abstract][Full Text] [Related]  

  • 19. EEG-CDILNet: a lightweight and accurate CNN network using circular dilated convolution for motor imagery classification.
    Liang T; Yu X; Liu X; Wang H; Liu X; Dong B
    J Neural Eng; 2023 Aug; 20(4):. PubMed ID: 37552978
    [No Abstract]   [Full Text] [Related]  

  • 20. Golden subject is everyone: A subject transfer neural network for motor imagery-based brain computer interfaces.
    Sun B; Wu Z; Hu Y; Li T
    Neural Netw; 2022 Jul; 151():111-120. PubMed ID: 35405471
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.