Automatic development of clinical prediction models with genetic programming: A case study in cardiovascular disease

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@Article{Bannister:2014:VH,
  author =       "C. A. Bannister and C. J. Currie and A. Preece and 
                 I. Spasic",
  title =        "Automatic development of clinical prediction models
                 with genetic programming: A case study in
                 cardiovascular disease",
  journal =      "Value in Health",
  volume =       "17",
  number =       "3",
  pages =        "A200--A201",
  year =         "2014",
  note =         "ISPOR 19th Annual International Meeting Research
                 Abstracts",
  keywords =     "genetic algorithms, genetic programming",
  ISSN =         "1098-3015",
  DOI =          "doi:10.1016/j.jval.2014.03.1171",
  URL =          "http://www.sciencedirect.com/science/article/pii/S1098301514012224",
  size =         "0.1 pages",
  abstract =     "Genetic programming is an Evolutionary Computing
                 technique, inspired by biological evolution, capable of
                 discovering complex non-linear patterns in large
                 datasets. Despite the potential advantages of genetic
                 programming over standard statistical methods, its
                 applications to survival analysis are at best rare,
                 primarily because of the difficulty in handling
                 censored data. The aim of this study was to demonstrate
                 the utility of genetic programming for the automatic
                 development of clinical prediction models using
                 cardiovascular disease as a case study.",
  notes =        "PRM115",
}

Genetic Programming entries for Christian Bannister Craig Currie A D Preece Irena Spasic

Citations