Double-Blind Comparison of Survival Analysis Models Using a Bespoke Web System

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

  author =       "A. F. G. Taktak and Christian Setzkorn and 
                 B. E. Damato",
  title =        "Double-Blind Comparison of Survival Analysis Models
                 Using a Bespoke Web System",
  booktitle =    "Engineering in Medicine and Biology Society, 2006.
                 EMBS '06. 28th Annual International Conference of the
  year =         "2006",
  pages =        "2466--2469",
  address =      "New York",
  month =        aug,
  publisher =    "IEEE",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/IEMBS.2006.259797",
  abstract =     "The aim of this study was to carry out a comparison of
                 different linear and non-linear models from different
                 centres on a common dataset in a double-blind manner to
                 eliminate bias. The dataset was shared over the
                 Internet using a secure bespoke environment called
                 geoconda. Models evaluated included: (1) Cox model, (2)
                 Log Normal model, (3) Partial Logistic Spline, (4)
                 Partial Logistic Artificial Neural Network and (5)
                 Radial Basis Function Networks. Graphical analysis of
                 the various models with the Kaplan-Meier values were
                 carried out in 3 survival groups in the test set
                 classified according to the TNM staging system. The
                 discrimination value for each model was determined
                 using the area under the ROC curve. Results showed that
                 the Cox model tended towards optimism whereas the
                 partial logistic Neural Networks showed slight
  notes =        "1557-170X",

Genetic Programming entries for Azzam F G Taktak Christian Setzkorn Bertil E Damato