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

Jeong Ho HanSo Jin YoonHye Sun LeeGoeun ParkJoo Hee LimJeong Eun ShinHo Seon EunMin Soo ParkSoon Min Lee
Published in: Yonsei medical journal (2022)
We have shown the possibility of predicting PGF through machine learning algorithms, especially XGB. Such models may help neonatologists in the early diagnosis of high-risk infants for PGF for early intervention.
Keyphrases
  • machine learning
  • low birth weight
  • preterm infants
  • human milk
  • artificial intelligence
  • preterm birth
  • big data
  • randomized controlled trial