BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

229 related articles for article (PubMed ID: 34084917)

  • 21. Channel selection and classification of electroencephalogram signals: an artificial neural network and genetic algorithm-based approach.
    Yang J; Singh H; Hines EL; Schlaghecken F; Iliescu DD; Leeson MS; Stocks NG
    Artif Intell Med; 2012 Jun; 55(2):117-26. PubMed ID: 22503644
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Backpropagation-Based Learning Techniques for Deep Spiking Neural Networks: A Survey.
    Dampfhoffer M; Mesquida T; Valentian A; Anghel L
    IEEE Trans Neural Netw Learn Syst; 2023 Apr; PP():. PubMed ID: 37027264
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Kernel Granger Causality Based on Back Propagation Neural Network Fuzzy Inference System on fMRI Data.
    Guo H; Zeng W; Shi Y; Deng J; Zhao L
    IEEE Trans Neural Syst Rehabil Eng; 2020 May; 28(5):1049-1058. PubMed ID: 32248114
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Neural Granger Causality.
    Tank A; Covert I; Foti N; Shojaie A; Fox EB
    IEEE Trans Pattern Anal Mach Intell; 2022 Aug; 44(8):4267-4279. PubMed ID: 33705309
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Inferring connectivity in networked dynamical systems: Challenges using Granger causality.
    Lusch B; Maia PD; Kutz JN
    Phys Rev E; 2016 Sep; 94(3-1):032220. PubMed ID: 27739857
    [TBL] [Abstract][Full Text] [Related]  

  • 26. A procedure to increase the power of Granger-causal analysis through temporal smoothing.
    Spencer E; Martinet LE; Eskandar EN; Chu CJ; Kolaczyk ED; Cash SS; Eden UT; Kramer MA
    J Neurosci Methods; 2018 Oct; 308():48-61. PubMed ID: 30031776
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Hybrid Regularized Echo State Network for Multivariate Chaotic Time Series Prediction.
    Xu M; Han M; Qiu T; Lin H
    IEEE Trans Cybern; 2019 Jun; 49(6):2305-2315. PubMed ID: 29994040
    [TBL] [Abstract][Full Text] [Related]  

  • 28. The boundaries of state-space Granger causality analysis applied to BOLD simulated data: A comparative modelling and simulation approach.
    Fernandes TT; Direito B; Sayal A; Pereira J; Andrade A; Castelo-Branco M
    J Neurosci Methods; 2020 Jul; 341():108758. PubMed ID: 32416276
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Identifying the pulsed neuron networks' structures by a nonlinear Granger causality method.
    Zhu MJ; Dong CY; Chen XY; Ren JW; Zhao XY
    BMC Neurosci; 2020 Feb; 21(1):7. PubMed ID: 32050908
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Neural networks with non-uniform embedding and explicit validation phase to assess Granger causality.
    Montalto A; Stramaglia S; Faes L; Tessitore G; Prevete R; Marinazzo D
    Neural Netw; 2015 Nov; 71():159-71. PubMed ID: 26356599
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Rethinking the performance comparison between SNNS and ANNS.
    Deng L; Wu Y; Hu X; Liang L; Ding Y; Li G; Zhao G; Li P; Xie Y
    Neural Netw; 2020 Jan; 121():294-307. PubMed ID: 31586857
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Macromolecular crowding: chemistry and physics meet biology (Ascona, Switzerland, 10-14 June 2012).
    Foffi G; Pastore A; Piazza F; Temussi PA
    Phys Biol; 2013 Aug; 10(4):040301. PubMed ID: 23912807
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Robust nonlinear autoregressive moving average model parameter estimation using stochastic recurrent artificial neural networks.
    Chon KH; Hoyer D; Armoundas AA; Holstein-Rathlou NH; Marsh DJ
    Ann Biomed Eng; 1999; 27(4):538-47. PubMed ID: 10468238
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Granger Causality Testing with Intensive Longitudinal Data.
    Molenaar PCM
    Prev Sci; 2019 Apr; 20(3):442-451. PubMed ID: 29858760
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Analyzing brain networks with PCA and conditional Granger causality.
    Zhou Z; Chen Y; Ding M; Wright P; Lu Z; Liu Y
    Hum Brain Mapp; 2009 Jul; 30(7):2197-206. PubMed ID: 18830956
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Evaluation of Directed Causality Measures and Lag Estimations in Multivariate Time-Series.
    Heyse J; Sheybani L; Vulliémoz S; van Mierlo P
    Front Syst Neurosci; 2021; 15():620338. PubMed ID: 34744643
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Comprehensive study on applications of artificial neural network in food process modeling.
    Bhagya Raj GVS; Dash KK
    Crit Rev Food Sci Nutr; 2022; 62(10):2756-2783. PubMed ID: 33327740
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Multiscale Granger causality.
    Faes L; Nollo G; Stramaglia S; Marinazzo D
    Phys Rev E; 2017 Oct; 96(4-1):042150. PubMed ID: 29347576
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Causality analysis of neural connectivity: critical examination of existing methods and advances of new methods.
    Hu S; Dai G; Worrell GA; Dai Q; Liang H
    IEEE Trans Neural Netw; 2011 Jun; 22(6):829-44. PubMed ID: 21511564
    [TBL] [Abstract][Full Text] [Related]  

  • 40. A self-organized recurrent neural network for estimating the effective connectivity and its application to EEG data.
    Abbasvandi Z; Nasrabadi AM
    Comput Biol Med; 2019 Jul; 110():93-107. PubMed ID: 31132528
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 12.