Developing a logistic regression model to predict spontaneous preterm birth from maternal socio-demographic and obstetric history at initial pregnancy registration

Developing a logistic regression model to predict spontaneous preterm birth from maternal socio-demographic and obstetric history at initial pregnancy registration

Abstract Background Current predictive machine learning techniques for spontaneous preterm birth heavily rely on a history of previous preterm birth and/or costly techniques such as fetal fibronectin and ultrasound measurement of cervical length to the disadvantage of those considered at low risk an...

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Bibliographic Details
Main Authors: Brenda F. Narice, Mariam Labib, Mengxiao Wang, Victoria Byrne, Joanna Shepherd, Z. Q. Lang, Dilly OC Anumba
Format: Article
Language:English
Published: BMC 2024-10-01
Series:BMC Pregnancy and Childbirth
Subjects:
Preterm birth
Pregnancy
Prediction
Logistic regression model
Machine learning
Online Access:https://doi.org/10.1186/s12884-024-06892-3
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https://doi.org/10.1186/s12884-024-06892-3

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