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Related Experiment Video

Updated: Jun 3, 2025

A Common Marmoset Model of Mother-Infant Intervention for Breastfeeding Disorders in the Presence of Paternal Inhibition and Maternal Neglect
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Predicting early cessation of exclusive breastfeeding using machine learning techniques.

Freja Marie Nejsum1, Rikke Wiingreen1,2, Andreas Kryger Jensen3,4

  • 1Department of Pediatrics, Copenhagen University Hospital-North Zealand, Hillerød, Denmark.

Plos One
|January 9, 2025
PubMed
Summary

Machine learning models were developed to predict early breastfeeding cessation. However, the models showed limited accuracy, indicating that current predictive factors are insufficient for identifying mothers needing support.

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Area of Science:

  • Public Health
  • Maternal and Child Health
  • Biostatistics

Background:

  • Early cessation of exclusive breastfeeding impacts infant health and requires targeted support.
  • Machine learning (ML) offers potential for developing transparent, clinically applicable prediction models.
  • Identifying mothers at risk for early breastfeeding cessation is crucial for timely interventions.

Purpose of the Study:

  • To develop and validate two ML models predicting exclusive breastfeeding cessation within one month post-birth.
  • To assess the impact of including additional pregnancy and delivery complication factors on predictive accuracy.

Main Methods:

  • Random forest ML algorithm applied to a nationwide Danish birth cohort (2014-2015).
  • Model 1: 11 established factors; Model 2: Model 1 factors + 21 additional complication factors.
  • Feature importance analysis used to identify key predictors.

Main Results:

  • Dataset included 110,206 infants and 106,835 mothers.
  • Model 1 AUC: 62.0%; Accuracy: 60.4%. Model 2 AUC: 62.2%; Accuracy: 60.0%.
  • Key predictors included birthplace, maternal education, delivery mode, and maternal BMI.

Conclusions:

  • The developed ML models demonstrated limited accuracy in predicting early breastfeeding cessation.
  • Expanding the models with additional pregnancy and delivery factors did not significantly improve predictive performance.
  • Further research is needed to identify more robust predictors for early breastfeeding cessation.