BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

188 related articles for article (PubMed ID: 24211917)

  • 1. A novel classification method based on ICA and ELM: a case study in lie detection.
    Xiong Y; Luo Y; Huang W; Zhang W; Yang Y; Gao J
    Biomed Mater Eng; 2014; 24(1):357-63. PubMed ID: 24211917
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A novel concealed information test method based on independent component analysis and support vector machine.
    Gao J; Lu L; Yang Y; Yu G; Na L; Rao N
    Clin EEG Neurosci; 2012 Jan; 43(1):54-63. PubMed ID: 22423552
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A novel approach for lie detection based on F-score and extreme learning machine.
    Gao J; Wang Z; Yang Y; Zhang W; Tao C; Guan J; Rao N
    PLoS One; 2014; 8(6):e64704. PubMed ID: 23755136
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Denoised P300 and machine learning-based concealed information test method.
    Gao J; Yan X; Sun J; Zheng C
    Comput Methods Programs Biomed; 2011 Dec; 104(3):410-7. PubMed ID: 21126796
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Epileptic EEG classification based on extreme learning machine and nonlinear features.
    Yuan Q; Zhou W; Li S; Cai D
    Epilepsy Res; 2011 Sep; 96(1-2):29-38. PubMed ID: 21616643
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A novel algorithm to enhance P300 in single trials: application to lie detection using F-score and SVM.
    Gao J; Tian H; Yang Y; Yu X; Li C; Rao N
    PLoS One; 2014; 9(11):e109700. PubMed ID: 25365325
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Classification of mental tasks from EEG signals using extreme learning machine.
    Liang NY; Saratchandran P; Huang GB; Sundararajan N
    Int J Neural Syst; 2006 Feb; 16(1):29-38. PubMed ID: 16496436
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Direct Kernel Perceptron (DKP): ultra-fast kernel ELM-based classification with non-iterative closed-form weight calculation.
    Fernández-Delgado M; Cernadas E; Barro S; Ribeiro J; Neves J
    Neural Netw; 2014 Feb; 50():60-71. PubMed ID: 24287336
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Single-trial classification of EEG in a visual object task using ICA and machine learning.
    Stewart AX; Nuthmann A; Sanguinetti G
    J Neurosci Methods; 2014 May; 228():1-14. PubMed ID: 24613798
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Predicting variations of perceptual performance across individuals from neural activity using pattern classifiers.
    Das K; Giesbrecht B; Eckstein MP
    Neuroimage; 2010 Jul; 51(4):1425-37. PubMed ID: 20302949
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A hierarchical semi-supervised extreme learning machine method for EEG recognition.
    She Q; Hu B; Luo Z; Nguyen T; Zhang Y
    Med Biol Eng Comput; 2019 Jan; 57(1):147-157. PubMed ID: 30054779
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A new approach for EEG feature extraction in P300-based lie detection.
    Abootalebi V; Moradi MH; Khalilzadeh MA
    Comput Methods Programs Biomed; 2009 Apr; 94(1):48-57. PubMed ID: 19041154
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Sparse Bayesian extreme learning machine for multi-classification.
    Luo J; Vong CM; Wong PK
    IEEE Trans Neural Netw Learn Syst; 2014 Apr; 25(4):836-43. PubMed ID: 24807961
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Automatic removal of eye-movement and blink artifacts from EEG signals.
    Gao JF; Yang Y; Lin P; Wang P; Zheng CX
    Brain Topogr; 2010 Mar; 23(1):105-14. PubMed ID: 20039116
    [TBL] [Abstract][Full Text] [Related]  

  • 15. EEG classification approach based on the extreme learning machine and wavelet transform.
    Yuan Q; Zhou W; Zhang J; Li S; Cai D; Zeng Y
    Clin EEG Neurosci; 2012 Apr; 43(2):127-32. PubMed ID: 22715486
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Improving the separability of motor imagery EEG signals using a cross correlation-based least square support vector machine for brain-computer interface.
    Siuly S; Li Y
    IEEE Trans Neural Syst Rehabil Eng; 2012 Jul; 20(4):526-38. PubMed ID: 22287252
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Identification of temporal variations in mental workload using locally-linear-embedding-based EEG feature reduction and support-vector-machine-based clustering and classification techniques.
    Yin Z; Zhang J
    Comput Methods Programs Biomed; 2014 Jul; 115(3):119-34. PubMed ID: 24821400
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Classification of EEG signals using neural network and logistic regression.
    Subasi A; Erçelebi E
    Comput Methods Programs Biomed; 2005 May; 78(2):87-99. PubMed ID: 15848265
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Enabling computer decisions based on EEG input.
    Culpepper BJ; Keller RM
    IEEE Trans Neural Syst Rehabil Eng; 2003 Dec; 11(4):354-60. PubMed ID: 14960110
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Evolutionary optimization of classifiers and features for single-trial EEG discrimination.
    Aberg MC; Wessberg J
    Biomed Eng Online; 2007 Aug; 6():32. PubMed ID: 17716370
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.