Proposing a machine-learning based method to predict stillbirth before and during delivery and ranking the features: nationwide retrospective cross-sectional study

Proposing a machine-learning based method to predict stillbirth before and during delivery and ranking the features: nationwide retrospective cross-sectional study

Abstract Background Stillbirth is defined as fetal loss in pregnancy beyond 28 weeks by WHO. In this study, a machine-learning based method is proposed to predict stillbirth from livebirth and discriminate stillbirth before and during delivery and rank the features. Method A two-step stack ensemble...

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Bibliographic Details
Main Authors: Toktam Khatibi, Elham Hanifi, Mohammad Mehdi Sepehri, Leila Allahqoli
Format: Article
Language:English
Published: BMC 2021-03-01
Series:BMC Pregnancy and Childbirth
Subjects:
Stillbirth prediction
Classification
Feature selection
Ensemble learning
IMAN registry
Online Access:https://doi.org/10.1186/s12884-021-03658-z

Internet

https://doi.org/10.1186/s12884-021-03658-z

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