BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

281 related articles for article (PubMed ID: 23643311)

  • 1. EEG segmentation for improving automatic CAP detection.
    Mariani S; Grassi A; Mendez MO; Milioli G; Parrino L; Terzano MG; Bianchi AM
    Clin Neurophysiol; 2013 Sep; 124(9):1815-23. PubMed ID: 23643311
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Characterization of A phases during the cyclic alternating pattern of sleep.
    Mariani S; Manfredini E; Rosso V; Mendez MO; Bianchi AM; Matteucci M; Terzano MG; Cerutti S; Parrino L
    Clin Neurophysiol; 2011 Oct; 122(10):2016-24. PubMed ID: 21439902
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Efficient automatic classifiers for the detection of A phases of the cyclic alternating pattern in sleep.
    Mariani S; Manfredini E; Rosso V; Grassi A; Mendez MO; Alba A; Matteucci M; Parrino L; Terzano MG; Cerutti S; Bianchi AM
    Med Biol Eng Comput; 2012 Apr; 50(4):359-72. PubMed ID: 22430617
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A new quantitative automatic method for the measurement of non-rapid eye movement sleep electroencephalographic amplitude variability.
    Ferri R; Rundo F; Novelli L; Terzano MG; Parrino L; Bruni O
    J Sleep Res; 2012 Apr; 21(2):212-20. PubMed ID: 22084833
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Assessment of Itakura Distance as a valuable feature for computer-aided classification of sleep stages.
    Ebrahimi F; Mikaili M; Estrada E; Nazeran H
    Annu Int Conf IEEE Eng Med Biol Soc; 2007; 2007():3300-3. PubMed ID: 18002701
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Visual and automatic classification of the cyclic alternating pattern in electroencephalography during sleep.
    Largo R; Lopes MC; Spruyt K; Guilleminault C; Wang YP; Rosa AC
    Braz J Med Biol Res; 2019 Feb; 52(3):e8059. PubMed ID: 30810623
    [TBL] [Abstract][Full Text] [Related]  

  • 7. All-night EEG power spectral analysis of the cyclic alternating pattern components in young adult subjects.
    Ferri R; Bruni O; Miano S; Plazzi G; Terzano MG
    Clin Neurophysiol; 2005 Oct; 116(10):2429-40. PubMed ID: 16112901
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Automatic detection of a phases of the cyclic alternating pattern during sleep.
    Mariani S; Bianchi AM; Manfredini E; Rosso V; Mendez MO; Parrino L; Matteucci M; Grassi A; Cerutti S; Terzano MG
    Annu Int Conf IEEE Eng Med Biol Soc; 2010; 2010():5085-8. PubMed ID: 21096032
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Visual and automatic cyclic alternating pattern (CAP) scoring: inter-rater reliability study.
    Rosa A; Alves GR; Brito M; Lopes MC; Tufik S
    Arq Neuropsiquiatr; 2006 Sep; 64(3A):578-81. PubMed ID: 17119795
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A general automatic method for the analysis of NREM sleep microstructure.
    Barcaro U; Bonanni E; Maestri M; Murri L; Parrino L; Terzano MG
    Sleep Med; 2004 Nov; 5(6):567-76. PubMed ID: 15511703
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Automatic sleep stage classification based on EEG signals by using neural networks and wavelet packet coefficients.
    Ebrahimi F; Mikaeili M; Estrada E; Nazeran H
    Annu Int Conf IEEE Eng Med Biol Soc; 2008; 2008():1151-4. PubMed ID: 19162868
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Detection of cortical slow waves in the sleep EEG using a modified matching pursuit method with a restricted dictionary.
    Picot A; Whitmore H; Chapotot F
    IEEE Trans Biomed Eng; 2012 Oct; 59(10):2808-17. PubMed ID: 22868527
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Automatic sleep stage classification using two-channel electro-oculography.
    Virkkala J; Hasan J; Värri A; Himanen SL; Müller K
    J Neurosci Methods; 2007 Oct; 166(1):109-15. PubMed ID: 17681382
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Automatic sleep scoring: a search for an optimal combination of measures.
    Krakovská A; Mezeiová K
    Artif Intell Med; 2011 Sep; 53(1):25-33. PubMed ID: 21742473
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Learning machines and sleeping brains: Automatic sleep stage classification using decision-tree multi-class support vector machines.
    Lajnef T; Chaibi S; Ruby P; Aguera PE; Eichenlaub JB; Samet M; Kachouri A; Jerbi K
    J Neurosci Methods; 2015 Jul; 250():94-105. PubMed ID: 25629798
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Data-driven modeling of sleep states from EEG.
    Van Esbroeck A; Westover B
    Annu Int Conf IEEE Eng Med Biol Soc; 2012; 2012():5090-3. PubMed ID: 23367073
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Automatic detection of cyclic alternating pattern (CAP) sequences in sleep: preliminary results.
    Rosa AC; Parrino L; Terzano MG
    Clin Neurophysiol; 1999 Apr; 110(4):585-92. PubMed ID: 10378726
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Automatic A-Phase Detection of Cyclic Alternating Patterns in Sleep Using Dynamic Temporal Information.
    Hartmann S; Baumert M
    IEEE Trans Neural Syst Rehabil Eng; 2019 Sep; 27(9):1695-1703. PubMed ID: 31425039
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Inter-rater reliability of sleep cyclic alternating pattern (CAP) scoring and validation of a new computer-assisted CAP scoring method.
    Ferri R; Bruni O; Miano S; Smerieri A; Spruyt K; Terzano MG
    Clin Neurophysiol; 2005 Mar; 116(3):696-707. PubMed ID: 15721084
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A knowledge discovery methodology from EEG data for cyclic alternating pattern detection.
    Machado F; Sales F; Santos C; Dourado A; Teixeira CA
    Biomed Eng Online; 2018 Dec; 17(1):185. PubMed ID: 30563526
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 15.