On the Use of Deep Learning Decompositions and Physiological Measurements for the Prediction of Preterm Pregnancies in a Cohort of Patients in Active Labor

On the Use of Deep Learning Decompositions and Physiological Measurements for the Prediction of Preterm Pregnancies in a Cohort of Patients in Active Labor

Preterm pregnancies are one of the leading causes of morbidity and mortality amongst children under the age of five. This is a global issue and has been identified as an area requiring active research. The emphasis now is to identify and develop methods of predicting the likelihood of preterm birth....

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Bibliographic Details
Main Authors: Ejay Nsugbe, José Javier Reyes-Lagos, Dawn Adams, Oluwarotimi Williams Samuel, Mojisola Grace Asogbon, Michael Provost
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Engineering Proceedings
Subjects:
pregnancy
preterm
signal processing
LSDL
signal decomposition
obstetric medicine
Online Access:https://www.mdpi.com/2673-4591/27/1/20

Internet

https://www.mdpi.com/2673-4591/27/1/20

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