Analysis and Classification of Epilepsy Stages with Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Sotelo:2012:evolve,
  author =       "Arturo Sotelo and Enrique Guijarro and 
                 Leonardo Trujillo and Luis Coria and Yuliana Martinez",
  title =        "Analysis and Classification of Epilepsy Stages with
                 Genetic Programming",
  booktitle =    "EVOLVE - A Bridge between Probability, Set Oriented
                 Numerics, and Evolutionary Computation {II}",
  year =         "2012",
  editor =       "Oliver Schuetze and Carlos A. {Coello Coello} and 
                 Alexandru-Adrian Tantar and Emilia Tantar and 
                 Pascal Bouvry and Pierre {Del Moral} and Pierrick Legrand",
  volume =       "175",
  series =       "Advances in Intelligent Systems and Computing",
  pages =        "57--70",
  address =      "Mexico City, Mexico",
  month =        aug # " 7-9",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-642-31519-0",
  DOI =          "doi:10.1007/978-3-642-31519-0_4",
  abstract =     "Epilepsy is a widespread disorder that affects many
                 individuals worldwide. For this reason much work has
                 been done to develop computational systems that can
                 facilitate the analysis and interpretation of the
                 signals generated by a patients brain during the onset
                 of an epileptic seizure. Currently, this is done by
                 human experts since computational methods cannot
                 achieve a similar level of performance. This paper
                 presents a Genetic Programming (GP) based approach to
                 analyse brain activity captured with Electrocorticogram
                 (ECoG). The goal is to evolve classifiers that can
                 detect the three main stages of an epileptic seizure.
                 Experimental results show good performance by the
                 GP-classifiers, evaluated based on sensitivity,
                 specificity, prevalence and likelihood ratio. The
                 results are unique within this domain, and could become
                 a useful tool in the development of future treatment
                 methods.",
  notes =        "EVOLVE-2012",
  affiliation =  "Departamento de Ingenieria Electrica y Electronica,
                 Instituto Tecnologico de Tijuana, Blvd. Industrial y
                 Av. ITR Tijuana S/N, Mesa Otay, C.P. 22500 Tijuana,
                 B.C., Mexico",
}

Genetic Programming entries for Arturo Sotelo Enrique Guijarro Estelles Leonardo Trujillo Luis N Coria Yuliana Martinez

Citations