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Erschienen in: Archives of Gynecology and Obstetrics 5/2011

01.05.2011 | Materno-Fetal Medicine

Neural networks prediction of preterm delivery with first trimester bleeding

verfasst von: U. Elaveyini, S. Prasanna Devi, K. Suryaprakasa Rao

Erschienen in: Archives of Gynecology and Obstetrics | Ausgabe 5/2011

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Abstract

Objective

This paper illustrates a retrospective study of the outcome of those pregnancies that continued from an initial episode of bleeding in first trimester.

Methods

Neural networks is used for the prediction of preterm delivery, using various inputs such as the age of women, gestational age when the bleeding occurred, duration of the bleeding days, amount of bleeding, number of episodes, presence or absence of hematoma and placentation position.

Results

The success rate of prediction obtained using the feed forward backpropogation network is 70%. Hence, this model can be used to identify women at the risk of premature delivery for planning antenatal care and clinical interventions in pregnancy.
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Metadaten
Titel
Neural networks prediction of preterm delivery with first trimester bleeding
verfasst von
U. Elaveyini
S. Prasanna Devi
K. Suryaprakasa Rao
Publikationsdatum
01.05.2011
Verlag
Springer-Verlag
Erschienen in
Archives of Gynecology and Obstetrics / Ausgabe 5/2011
Print ISSN: 0932-0067
Elektronische ISSN: 1432-0711
DOI
https://doi.org/10.1007/s00404-010-1469-2

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