Predicting early cessation of exclusive breastfeeding using machine learning techniques.
<h4>Background</h4>Identification of mother-infant pairs predisposed to early cessation of exclusive breastfeeding is important for delivering targeted support. Machine learning techniques enable development of transparent prediction models that enhance clinical applicability. We aimed t...
Saved in:
Main Authors: | Freja Marie Nejsum, Rikke Wiingreen, Andreas Kryger Jensen, Ellen Christine Leth Løkkegaard, Bo Mølholm Hansen |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2025-01-01
|
Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0312238 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Early Cessation of Breastfeeding and Determinants: Time to Event Analysis
by: Ebrahim Babaee, et al.
Published: (2020-01-01) -
Cessation of Exclusive Breastfeeding and Determining Factors at the University of Gondar Comprehensive Specialized Hospital, Northwest Ethiopia
by: Bayew Kelkay, et al.
Published: (2020-01-01) -
Comparison of breastfeeding self-efficacy between exclusive and non-exclusive breastfeeding in postpartum women
by: Parvaneh Sarparastrazmju
Published: (2024-08-01) -
The Onset Lactation, Early Initiation Breastfeeding, and Frequency of Antenatal Care as Determinants of Successful Exclusive Breastfeeding in Primipara Mothers
by: Dian Shofiya, et al.
Published: (2024-12-01) -
Do Maternal Quality of Life and Breastfeeding Difficulties Influence the Continuation of Exclusive Breastfeeding?
by: Forough Mortazavi, et al.
Published: (2014-01-01)