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

Journal: BMC pregnancy and childbirth
PMID: 33653299

Abstract

BACKGROUND: This study introduced machine learning approaches to predict newborn's body mass index (BMI) based on ultrasound measures and maternal/delivery information.

Authors

  • Kwang-Sig Lee
    AI Center, Korea University College of Medicine, Seoul, South Korea.
  • Ho Yeon Kim
    Department of Obstetrics and Gynecology, Korea University College of Medicine, 73 Goryeodae-ro, Seongbuk-gu, Seoul, 02841, South Korea.
  • Se Jin Lee
    Department of Obstetrics and Gynecology, Kangwon National University Hospital, Kangwon National University School of Medicine, Kangwon, Chuncheon, South Korea.
  • Sung Ok Kwon
    Biomedical Research Institute, Kangwon National University Hospital, Chuncheon, Republic of Korea.
  • Sunghun Na
    Department of Obstetrics and Gynecology, Kangwon National University Hospital, Kangwon National University School of Medicine, Kangwon, Chuncheon, South Korea. lahun@kangwon.ac.kr.
  • Han Sung Hwang
    Department of Obstetrics and Gynecology, Research Institute of Medical Science, Konkuk University School of Medicine, Seoul, South Korea.
  • Mi Hye Park
    Department of Food Science and Nutrition, Kyungpook National University, Daegu 41566, Korea.
  • Ki Hoon Ahn
    Department of Obstetrics and Gynecology, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Korea. akh1220@korea.ac.kr.

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