Machine learning-based prediction model for spontaneous preterm birth in singleton pregnancies using mid-trimester cervical elastographic parameters

Jung, Y.; Heo, S.; Kwon, H.; Park, H.; Oh, S.; Sung, J.; Seol, H.; Kim, H.; Seong, W.; Hwang, H.; Jung, I.; Kwon, J.

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Machine learning-based prediction model for spontaneous preterm birth in singleton pregnancies using mid-trimester cervical elastographic parametersopen access

Authors: Jung, Y.; Heo, S.; Kwon, H.; Park, H.; Oh, S.; Sung, J.; Seol, H.; Kim, H.; Seong, W.; Hwang, H.; Jung, I.; Kwon, J.

Issue Date: Oct-2023

Publisher: WILEY

Citation: Ultrasound in Obstetrics & Gynecology, v.62, no.Suppl. 1, pp 34 - 35

Pages: 2

Indexed: SCIE
SCOPUS

Journal Title: Ultrasound in Obstetrics & Gynecology

Volume: 62

Number: Suppl. 1

Start Page: 34

End Page: 35

URI: https://scholarworks.dongguk.edu/handle/sw.dongguk/20634

DOI: 10.1002/uog.26416

ISSN: 0960-7692
1469-0705

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Appears in Collections: Graduate School > Department of Medicine > 1. Journal Articles

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