Ara es mostren els items 3-11 de 11

  • Feature and model selection in 1H-MRS single voxel spectra for cancer classification 

    González Navarro, Félix Fernando; Belanche Muñoz, Luis Antonio (Future Technology Press, 2009-01-31)
    Capítol de llibre
    Accés restringit per política de l'editorial
    Machine learning is a powerful paradigm within which to analyze 1HMRS spectral data for the classification of tumour pathologies. An important characteristic of this task is the high dimensionality of the involved data ...
  • Feature selection for microarray gene expression data using simulated annealing guided by the multivariate joint entropy 

    González Navarro, Félix Fernando; Belanche Muñoz, Luis Antonio (2013)
    Report de recerca
    Accés obert
    In this work a new way to calculate the multivariate joint entropy is presented. This measure is the basis for a fast information-theoretic based evaluation of gene relevance in a Microarray Gene Expression data context. ...
  • Feature selection for the prediction and visualization of brain tumor types using proton magnetic resonance spectroscopy data 

    González Navarro, Félix Fernando; Belanche Muñoz, Luis Antonio (Springer, 2012)
    Capítol de llibre
    Accés restringit per política de l'editorial
    In cancer diagnosis, classification of the different tumor types is of great importance. An accurate prediction of basic tumor types provides better treatment and may minimize the negative impact of incorrectly targeted ...
  • Feature selection in proton magnetic resonance spectroscopy data of brain tumors 

    González Navarro, Félix Fernando; Belanche Muñoz, Luis Antonio (Università degli Studi di Salerno, 2011)
    Text en actes de congrés
    Accés obert
    In cancer diagnosis, classification of the different tumor types is of great importance. An accurate prediction of different tumor types provides better treatment and may minimize the negative impact of incorrectly targeted ...
  • Gene discovery for facioscapulohumeral muscular dystrophy by machine learning techniques 

    González Navarro, Félix Fernando; Belanche Muñoz, Luis Antonio; Gámez Moreno, María G.; Flores Ríos, Brenda L.; Ibarra Esquer, Jorge E.; López Morteo, Gabriel A. (2015-12-01)
    Article
    Accés obert
    Facioscapulohumeral muscular dystrophy (FSHD) is a neuromuscular disorder that shows a preference for the facial, shoulder and upper arm muscles. FSHD affects about one in 20-400,000 people, and no effective therapeutic ...
  • Machine learning methods for classifying normal vs. tumorous tissue with spectral data 

    González Navarro, Félix Fernando; Belanche Muñoz, Luis Antonio (2009)
    Text en actes de congrés
    Accés obert
    Machine learning is a powerful paradigm within which to analyze 1H-MRS spectral data for the automated classi¯cation of tumor pathologies aimed to facilitate clinical diagnosis. The high dimensionality of the involved ...
  • Parsimonious selection of useful genes in microarray gene expression data 

    González Navarro, Félix Fernando; Belanche Muñoz, Luis Antonio (Springer, 2011)
    Capítol de llibre
    Accés obert
    Machine Learning methods have of late made significant efforts to solving multidisciplinary problems in the field of cancer classification in microarray gene expression data. These tasks are characterized by a large number ...
  • Using machine learning techniques to explore 1H-MRS data of brain tumors 

    González Navarro, Félix Fernando; Belanche Muñoz, Luis Antonio (IEEE Computer Society Publications, 2009)
    Text en actes de congrés
    Accés obert
    Machine learning is a powerful paradigm to analyze Proton Magnetic Resonance Spectroscopy (1H-MRS) spectral data for the classification of brain tumor pathologies. An important characteristic of this task is the high ...
  • Using machine learning techniques to explore H-1-MRS data of brain tumors 

    González Navarro, Félix Fernando; Belanche Muñoz, Luis Antonio (IEEE Computer Society Publications, 2009)
    Text en actes de congrés
    Accés obert
    Machine learning is a powerful paradigm to analyze Proton Magnetic Resonance Spectroscopy (1H-MRS) spectral data for the classification of brain tumor pathologies. An important characteristic of this task is the high ...