Modelling Medical Time Series Using Grammar-Guided Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  title =        "Modelling Medical Time Series Using Grammar-Guided
                 Genetic Programming",
  author =       "Fernando Alonso and Loic Martinez and 
                 Aurora Perez-Perez and Agustin Santamaria and 
                 Juan Pedro Valente",
  bibdate =      "2010-02-01",
  bibsource =    "DBLP,
  booktitle =    "8th Industrial Conference in Data Mining, Medical
                 Applications, E-Commerce, Marketing and Theoretical
                 Aspects, ICDM 2008",
  publisher =    "Springer",
  year =         "2008",
  volume =       "5077",
  editor =       "Petra Perner",
  isbn13 =       "978-3-540-70717-2",
  pages =        "32--46",
  series =       "Lecture Notes in Computer Science",
  DOI =          "doi:10.1007/978-3-540-70720-2_3",
  address =      "Leipzig, Germany",
  month =        jul # " 16-18",
  keywords =     "genetic algorithms, genetic programming, Time series
                 characterization, isokinetics, symbolic distance,
                 information extraction, reference model, text mining",
  size =         "15 pages",
  abstract =     "The analysis of time series is extremely important in
                 the field of medicine, because this is the format of
                 many medical data types. Most of the approaches that
                 address this problem are based on numerical algorithms
                 that calculate distances, clusters, reference models,
                 etc. However, a symbolic rather than numerical analysis
                 is sometimes needed to search for the characteristics
                 of time series. Symbolic information helps users to
                 efficiently analyse and compare time series in the same
                 or in a similar way as a domain expert would. This
                 paper describes the definition of the symbolic domain,
                 the process of converting numerical into symbolic time
                 series and a distance for comparing symbolic temporal
                 sequences. Then, the paper focuses on a method to
                 create the symbolic reference model for a certain
                 population using grammar-guided genetic programming.
                 The work is applied to the isokinetics domain within an
                 application called I4.",
  notes =        "Context Free Grammar",

Genetic Programming entries for Fernando Alonso Loic Martinez Normand Aurora Perez-Perez Agustin Santamaria Juan Pedro Caraca-valente Hernandez