Application of Machine Learning Approaches to Predict Postnatal Growth Failure in Very Low Birth Weight Infants.

Abstract

Authors

• Jung Ho Han
  Department of Pediatrics, Yonsei University College of Medicine, Seoul, Korea.
• So Jin Yoon
  Department of Pediatrics, Yonsei University College of Medicine, Seoul, Korea.
• Hye Sun Lee
  Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, Korea (G.R.K., E.-K.K., J.H.Y., H.J.M., J.Y.K.); Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, Seoul, Korea (S.J.K.); Department of Radiology, Ajou University School of Medicine, Suwon, Korea (E.J.H.); Yonsei University College of Medicine, Seoul, Korea (J.Y.); and Department of Research Affairs, Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Korea (H.S.L., J.H.H.).
• Goeun Park
  Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, South Korea.
• Joohee Lim
  Department of Pediatrics, Yonsei University College of Medicine, Seoul, Korea.
• Jeong Eun Shin
  Department of Pediatrics, Yonsei University College of Medicine, Seoul, Korea.
• Ho Seon Eun
  Department of Pediatrics, Yonsei University College of Medicine, Seoul, Korea.
• Min Soo Park
  Department of Pediatrics, Yonsei University College of Medicine, Seoul, Korea.
• Soon Min Lee
  Department of Pediatrics, Yonsei University College of Medicine, Seoul, Korea. smlee@yuhs.ac.

Keywords

External Resources