Comparison of logistic regression with machine learning methods for the prediction of fetal growth abnormalities: a retrospective cohort study

S Kuhle, B Maguire, H Zhang, D Hamilton… - BMC pregnancy and …, 2018 - Springer
Background While there is increasing interest in identifying pregnancies at risk for adverse
outcome, existing prediction models have not adequately assessed population-based risks …

Machine learning for fetal growth prediction

AI Naimi, RW Platt, JC Larkin - Epidemiology, 2018 - journals.lww.com
Birthweight is often used as a proxy for fetal weight. Problems with this practice have
recently been brought to light. We explore whether data available at birth can be used to …

Prediction of small for gestational age neonates: screening by maternal factors, fetal biometry, and biomarkers at 35–37 weeks' gestation

A Ciobanu, A Rouvali, A Syngelaki, R Akolekar… - American Journal of …, 2019 - Elsevier
Background Small for gestational age (SGA) neonates are at increased risk for perinatal
mortality and morbidity; however, the risks can be substantially reduced if the condition is …

Small-for-gestational age and large-for-gestational age thresholds to predict infants at risk of adverse delivery and neonatal outcomes: are current charts adequate …

T Norris, W Johnson, D Farrar, D Tuffnell, J Wright… - BMJ open, 2015 - bmjopen.bmj.com
Objectives Construct an ethnic-specific chart and compare the prediction of adverse
outcomes using this chart with the clinically recommended UK-WHO and customised birth …

Tracking of fetal growth characteristics during different trimesters and the risks of adverse birth outcomes

R Gaillard, EAP Steegers, JC de Jongste… - International journal …, 2014 - academic.oup.com
Background: Fetal growth characteristics are used to identify influences of several maternal
characteristics and to identify individuals at increased risk of adverse outcomes. The extent …

Prediction of preterm birth in nulliparous women using logistic regression and machine learning

R Arabi Belaghi, J Beyene, SD McDonald - PLoS One, 2021 - journals.plos.org
Objective To predict preterm birth in nulliparous women using logistic regression and
machine learning. Design Population-based retrospective cohort. Participants Nulliparous …

Adverse neonatal outcomes: examining the risks between preterm, late preterm, and term infants

JA Bastek, MD Sammel, E Paré, SK Srinivas… - American journal of …, 2008 - Elsevier
OBJECTIVE: There is a relative paucity of data regarding neonatal outcomes in the late
preterm cohort (34 to 36 6/7 weeks). This study sought to assess differences in adverse …

First trimester prediction of small‐and large‐for‐gestation neonates by an integrated model incorporating ultrasound parameters, biochemical indices and maternal …

I Papastefanou, AP Souka, A Pilalis… - Acta obstetricia et …, 2012 - Wiley Online Library
Objective. To identify maternal/pregnancy characteristics, first trimester ultrasound
parameters and biochemical indices which are significant independent predictors of small …

Risk assessment of adverse birth outcomes in relation to maternal age

YH Weng, CY Yang, YW Chiu - PloS one, 2014 - journals.plos.org
Background Although a number of studies have investigated correlations of maternal age
with birth outcomes, an extensive assessment using age as a continuous variable is lacking …

Prediction of fetal growth restriction using estimated fetal weight vs a combined screening model in the third trimester

J Miranda, M Rodriguez‐Lopez… - … in obstetrics & …, 2017 - Wiley Online Library
Objectives To compare the performance of third‐trimester screening, based on estimated
fetal weight centile (EFWc) vs a combined model including maternal baseline …