Now showing items 6-9 of 9

  • Machine learning methods for classifying normal vs. tumorous tissue with spectral data 

    González Navarro, Félix Fernando; Belanche Muñoz, Luis Antonio (2009)
    Conference report
    Open Access
    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)
    Part of book or chapter of book
    Open Access
    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)
    Conference report
    Open Access
    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)
    Conference report
    Open Access
    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 ...