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An ordinal classification approach for CTG categorization
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0001-9701-4203
Laboratory of Knowledge and Intelligent Computing, Department of Computer Engineering, Technological Educational Institute of Epirus.
Department of Electrical Engineering and Computer Technology, University of Patras.
Laboratory of Knowledge and Intelligent Computing, Department of Computer Engineering, TEI of Epirus, Artas, Kostakioi.
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2017 (English)In: 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Piscataway, NJ: IEEE, 2017, p. 2642-2645, article id 8037400Conference paper, Published paper (Refereed)
Abstract [en]

Evaluation of cardiotocogram (CTG) is a standard approach employed during pregnancy and delivery. But, its interpretation requires high level expertise to decide whether the recording is Normal, Suspicious or Pathological. Therefore, a number of attempts have been carried out over the past three decades for development automated sophisticated systems. These systems are usually (multiclass) classification systems that assign a category to the respective CTG. However most of these systems usually do not take into consideration the natural ordering of the categories associated with CTG recordings. In this work, an algorithm that explicitly takes into consideration the ordering of CTG categories, based on binary decomposition method, is investigated. Achieved results, using as a base classifier the C4.5 decision tree classifier, prove that the ordinal classification approach is marginally better than the traditional multiclass classification approach, which utilizes the standard C4.5 algorithm for several performance criteria.

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE, 2017. p. 2642-2645, article id 8037400
Series
ROCEEDINGS OF ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, ISSN 1094-687X
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-65661DOI: 10.1109/EMBC.2017.8037400ISI: 000427085303022Scopus ID: 2-s2.0-85032187388ISBN: 978-1-5090-2809-2 (electronic)OAI: oai:DiVA.org:ltu-65661DiVA, id: diva2:1141600
Conference
39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC),Jeju Island, South Korea, 11-15 July 2017
Available from: 2017-09-15 Created: 2017-09-15 Last updated: 2018-04-19Bibliographically approved

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Georgoulas, GeorgiosNikolakopoulos, George

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CiteExportLink to record
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  • apa
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