Fetal Weight Prediction Models: Standard Techniques or Computational Intelligence Methods?

  • Authors:
  • Tomáš Siegl;Pavel Kordík;Miroslav Šnorek;Pavel Calda

  • Affiliations:
  • Department of Computer Science and Engineering, FEE, Czech Technical University, Prague, Czech Republic;Department of Computer Science and Engineering, FEE, Czech Technical University, Prague, Czech Republic;Department of Computer Science and Engineering, FEE, Czech Technical University, Prague, Czech Republic;Department of Computer Science and Engineering, FEE, Czech Technical University, Prague, Czech Republic

  • Venue:
  • ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part I
  • Year:
  • 2008

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Abstract

An accurate model of ultrasound estimation of fetal weight (EFW) can help in decision if the cesarean childbirth is necessary. We collected models from various sources and compared their accuracy. These models were mostly obtained by standard techniques such as linear and nonlinear regression. The aim of the comparison was to recommend a model best fitting to data measured for Czech population. Alternatively, we generated several linear and non-linear models by using our method GAME from the computational intelligence domain. GAME models can be serialized into simple equations that are understandable by domain experts. In this contribution, we show that automatically generated GAME models are at least as accurate (in terms of root mean squared error and standard deviations of predictions) as the best model computed by means of (time and expert skills demanding) standard techniques.