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Combining latent class analysis labeling with multiclass approach for fetal heart rate categorization
Laboratory of Knowledge and Intelligent Computing, Department of Computer Engineering, Technological Educational Institute of Epirus.
Department of Cybernetics, FEE, Czech Technical University in Prague.
Laboratory of Knowledge and Intelligent Computing, Department of Computer Engineering, Technological Educational Institute of Epirus.ORCID-id: 0000-0001-9701-4203
Department of Cybernetics, FEE, Czech Technical University in Prague.
Vise andre og tillknytning
2015 (engelsk)Inngår i: Physiological Measurement, ISSN 0967-3334, E-ISSN 1361-6579, Vol. 36, nr 5, s. 1001-1024, artikkel-id 1001Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

The most common approach to assess fetal well-being during delivery is monitoring of fetal heart rate and uterine contractions - the cardiotocogram (CTG). Nevertheless, 40 years since the introduction of CTG to clinical practice, its evaluation is still challenging with high inter- and intra-observer variability. Therefore the development of more objective methods has become an issue of major importance in the field. Unlike the usually proposed approaches to assign classes for classification methods that rely either on biochemical parameters (e.g. pH value) or a simple aggregation of expert judgment, this work investigates the use of an alternative labeling system using latent class analysis (LCA) along with an ordinal classification scheme. The study is performed on a well-documented open-access database, where nine expert obstetricians provided CTG annotations. The LCA is proposed here to produce more objective class labels while the ordinal classification aims to explore the natural ordering, and representation of increased severity, for obtaining the final results. The results are promising suggesting that more effort should be put into this proposed approach.

sted, utgiver, år, opplag, sider
Institute of Physics (IOP), 2015. Vol. 36, nr 5, s. 1001-1024, artikkel-id 1001
HSV kategori
Forskningsprogram
Reglerteknik
Identifikatorer
URN: urn:nbn:se:ltu:diva-66352DOI: 10.1088/0967-3334/36/5/1001PubMedID: 25894994Scopus ID: 2-s2.0-84929658662OAI: oai:DiVA.org:ltu-66352DiVA, id: diva2:1154190
Tilgjengelig fra: 2017-11-01 Laget: 2017-11-01 Sist oppdatert: 2017-11-24bibliografisk kontrollert

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