NDLI: Prediction of newborn’s body mass index using nationwide multicenter ultrasound data: a machine-learning study

Content Provider	Springer Nature : BioMed Central
Author	Lee, Kwang-Sig Kim, Ho Yeon Lee, Se Jin Kwon, Sung Ok Na, Sunghun Hwang, Han Sung Park, Mi Hye Ahn, Ki Hoon
Abstract	Background This study introduced machine learning approaches to predict newborn’s body mass index (BMI) based on ultrasound measures and maternal/delivery information. Methods Data came from 3159 obstetric patients and their newborns enrolled in a multi-center retrospective study. Variable importance, the effect of a variable on model performance, was used for identifying major predictors of newborn’s BMI among ultrasound measures and maternal/delivery information. The ultrasound measures included biparietal diameter (BPD), abdominal circumference (AC) and estimated fetal weight (EFW) taken three times during the week 21 - week 35 of gestational age and once in the week 36 or later. Results Based on variable importance from the random forest, major predictors of newborn’s BMI were the first AC and EFW in the week 36 or later, gestational age at delivery, the first AC during the week 21 - the week 35, maternal BMI at delivery, maternal weight at delivery and the first BPD in the week 36 or later. For predicting newborn’s BMI, linear regression (2.0744) and the random forest (2.1610) were better than artificial neural networks with one, two and three hidden layers (150.7100, 154.7198 and 152.5843, respectively) in the mean squared error. Conclusions This is the first machine-learning study with 64 clinical and sonographic markers for the prediction of newborns’ BMI. The week 36 or later is the most effective period for taking the ultrasound measures and AC and EFW are the best predictors of newborn’s BMI alongside gestational age at delivery and maternal BMI at delivery.
Related Links	https://bmcpregnancychildbirth.biomedcentral.com/counter/pdf/10.1186/s12884-021-03660-5.pdf
Ending Page	10
Page Count	10
Starting Page	1
File Format	HTM / HTML
ISSN	14712393
DOI	10.1186/s12884-021-03660-5
Journal	BMC Pregnancy and Childbirth
Issue Number	1
Volume Number	21
Language	English
Publisher	BioMed Central
Publisher Date	2021-03-02
Access Restriction	Open
Subject Keyword	Reproductive Medicine Maternal and Child Health Gynecology Newborn Body mass index Estimated fetal weight Abdominal circumference
Content Type	Text
Resource Type	Article
Subject	Obstetrics and Gynecology
Journal Impact Factor	2.8/2023
5-Year Journal Impact Factor	3.4/2023

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