A three class treatment of the FHR classification problem using latent class analysis labeling

Annu Int Conf IEEE Eng Med Biol Soc. 2014:2014:46-9. doi: 10.1109/EMBC.2014.6943525.

Abstract

Electronic Fetal Monitoring in the form of cardiotocography is routinely used for fetal assessment both during pregnancy and delivery. However its interpretation requires a high level of expertise and even then the assessment is somewhat subjective as it has been proven by the high inter and intra-observer variability. Therefore the scientific community seeks for more objective methods for its interpretation. Along this path, presented work proposes a classification approach, which is based on a latent class analysis method that attempts to produce more objective labeling of the training cases, a step which is vital in a classification problem. The method is combined with a simple logistic regression approach under two different schemes: a standard multi-class classification formulation and an ordinal classification one. The results are promising suggesting that more effort should be put in this proposed approach.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Cardiotocography
  • Databases as Topic
  • Female
  • Heart Rate, Fetal / physiology*
  • Humans
  • Likelihood Functions
  • Logistic Models
  • Pregnancy
  • Probability