title: A three class treatment of the FHR classification problem using latent class analysis labeling.
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.
authors.forename: George
authors.initials: G
authors.lastname: Georgoulas
authors.forename: Jiří
authors.initials: J
authors.lastname: Spilka
authors.forename: Petros
authors.initials: P
authors.lastname: Karvelis
authors.forename: Václav
authors.initials: V
authors.lastname: Chudáček
authors.forename: Chrysostomos
authors.initials: C
authors.lastname: Stylios
authors.forename: Lenka
authors.initials: L
authors.lastname: Lhotská
mesh_terms: D000465:Algorithms; D015148:Cardiotocography; D019992:Databases as Topic; D005260:Female; D006340:Heart Rate, Fetal / Q000502:physiology*; D006801:Humans; D016013:Likelihood Functions; D016015:Logistic Models; D011247:Pregnancy; D011336:Probability