Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Discriminating normal from "abnormal" pregnancy cases using an automated FHR evaluation method
Department of Cybernetics, Czech Technical University.
Laboratory of Knowledge and Intelligent Computing, Technological Educational Institute of Epirus, Department of Computer Engineering, Arta.ORCID iD: 0000-0001-9701-4203
Laboratory of Knowledge and Intelligent Computing, Department of Computer Engineering, Technological Educational Institute of Epirus.
Department of Cybernetics, Czech Technical University.
Show others and affiliations
2014 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Electronic fetal monitoring has become the gold standard for fetal assessment both during pregnancy as well as during delivery. Even though electronic fetal monitoring has been introduced to clinical practice more than forty years ago, there is still controversy in its usefulness especially due to the high inter- and intra-observer variability. Therefore the need for a more reliable and consistent interpretation has prompted the research community to investigate and propose various automated methodologies. In this work we propose the use of an automated method for the evaluation of fetal heart rate, the main monitored signal, which is based on a data set, whose labels/annotations are determined using a mixture model of clinical annotations. The successful results of the method suggest that it could be integrated into an assistive technology during delivery.

Place, publisher, year, edition, pages
Springer, 2014. p. 521-531
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 8445
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-68094DOI: 10.1007/978-3-319-07064-3_45Scopus ID: 2-s2.0-84900552330ISBN: 9783319070636 (print)OAI: oai:DiVA.org:ltu-68094DiVA, id: diva2:1193856
Conference
8th Hellenic Conference on Artificial Intelligence: Methods and Applications, SETN 2014, Ioannina, Greece, 15-17 May 2014
Available from: 2018-03-28 Created: 2018-03-28 Last updated: 2018-03-28Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Georgoulas, Georgios
Control Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf