Fuzzy Neural Network-based Fetal Health Monitoring using Cardiotocography Data

Fuzzy neural networkshave been widelyapplied in the medical field. In this paper, we apply cascade architectures of fuzzy neural networks to monitoring fetal health using Cardiotocography data. Cascade architectures of neural networks can select reduced size of input subspace by selecting useful inputs. For the optimization of the input subspace and the structure of the cascade architectures of fuzzy neural networks, genetic algorithms and gradient decent method are used. To verify the applicability of the proposed method, Cardiotocography data available on the Machine Learning Repository site at the University of California at Irvine is used.