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Predicting risk of early discontinuation of exclusive breastfeeding at a Brazilian referral hospital for high-risk neonates and infants: a decision-tree analysis.

Maíra Domingues Bernardes SilvaRaquel de Vasconcellos Carvalhaes de OliveiraDavi da Silveira Barroso AlvesEnirtes Caetano Prates Melo
Published in: International breastfeeding journal (2021)
The combination algorithm of decision trees (a machine learning technique) provides a better understanding of the risk predictors of breastfeeding cessation in a setting with a large variability in expositions. Decision trees may provide a basis for recommendations aimed at this high-risk population, within the Brazilian context, in light of the hospital stay at a neonatal unit and period of continuous feeding practice.
Keyphrases
  • machine learning
  • healthcare
  • decision making
  • preterm infants
  • primary care
  • acute care
  • deep learning
  • low birth weight
  • adverse drug
  • artificial intelligence
  • big data
  • quality improvement
  • emergency department