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Archives of Gynecology and Obstetrics

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01-05-2011 | Materno-Fetal Medicine

Neural networks prediction of preterm delivery with first trimester bleeding

Authors: U. Elaveyini, S. Prasanna Devi, K. Suryaprakasa Rao

Published in: Archives of Gynecology and Obstetrics | Issue 5/2011

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.

Available only for authorised users

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10.

Stefan Hausler, tutorial on neural networks toolbox available at http://www.igi.tugraz.at/lehre/EW/tutorials/nnt_intro/nnt_intro.pdf

Title: Neural networks prediction of preterm delivery with first trimester bleeding
Authors: U. Elaveyini
S. Prasanna Devi
K. Suryaprakasa Rao
Publication date: 01-05-2011
Publisher: Springer-Verlag
Published in: Archives of Gynecology and Obstetrics / Issue 5/2011
Print ISSN: 0932-0067
Electronic ISSN: 1432-0711
DOI: https://doi.org/10.1007/s00404-010-1469-2

Keynote webinar | Spotlight on sleep in brain health

Springer Medicine

Neural networks prediction of preterm delivery with first trimester bleeding

Abstract

Objective

Methods

Results

Keynote webinar | Spotlight on sleep in brain health

Springer Medicine

Abstract

Objective

Methods

Results

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