Predicting early cessation of exclusive breastfeeding using machine learning techniques

The two models could not accurately predict cessation of exclusive breastfeeding within one month among infants born after 35 weeks gestation. Contrary to our expectations, including additional factors in the model did not increase model performance.

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Publication Details

Journal
PLoS ONE
Published
2025-01-09
DOI
https://doi.org/10.1371/journal.pone.0312238
Citations
2
Primary Topic
Breastfeeding Practices and Influences
Type
article
Field-Weighted Citation Impact
2.71
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article

Predicting early cessation of exclusive breastfeeding using machine learning techniques

Bo Mølholm Hansen, Andreas Kryger Jensen, Rikke Wiingreen, Ellen Løkkegaard et al.
2 citations
PLoS ONE
Breastfeeding Practices and Influences
2.71
article

Predicting early cessation of exclusive breastfeeding using machine learning techniques

Bo Mølholm Hansen, Andreas Kryger Jensen, Rikke Wiingreen, Ellen Løkkegaard, Freja Marie Nejsum
article en
2 citations

Abstract

The two models could not accurately predict cessation of exclusive breastfeeding within one month among infants born after 35 weeks gestation. Contrary to our expectations, including additional factors in the model did not increase model performance.

PLoS ONEVol. 20(1)
University of Copenhagen (DK), Copenhagen University Hospital (DK), Zealand University Hospital (DK)
Good health and well-being
Openalex Percentile: Top 13%
Breastfeeding Practices and Influences
2.71
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Predicting early cessation of exclusive breastfeeding using machine learning techniques — Bo Mølholm Hansen, Andreas Kryger Jensen, et al. · PLoS ONE (2025) | TGRS Research Map | TGRS