• Ayfer Açikgöz, Merve Çakirli, Berrak Mizrak Şahin, and Özer Çelik.
• Department of Child Health and Disease Nursing, Eskisehir Osmangazi University Health Sciences, Eskisehir, Turkey.
• J Eval Clin Pract. 2024 Sep 1; 30 (6): 100010071000-1007.

BackgroundMachine learning techniques (MLT) build models to detect complex patterns and solve new problems using big data.AimThe present study aims to create a prediction interface for mothers breastfeeding exclusively for the first 6 months using MLT.MethodAll mothers who had babies aged 6-24 months between 15.09.2021 and 15.12.2021 and to whom the surveys could be delivered were included. 'Personal Information Form' created by the researchers was used as a data collection tool. Data from 514 mothers participating in the study were used for MLT. Data from 70% of mothers were used for educational purposes, and a prediction model was created. The data obtained from the remaining 30% of the mothers were used for testing.ResultsThe best MLT algorithm for predicting exclusive breastfeeding for the first 6 months was determined to be the Random Forest Classifier. The top five variables affecting the possibility of mothers breastfeeding exclusively for the first 6 months were as follows: "the mother not having any health problems during pregnancy," "there were no people who negatively affected the mother's morale about breastfeeding," "the amount of water the mother drinks in a day," "thinking that her milk supply is insufficient," "having no problems breastfeeding the baby".ConclusionsUsing created prediction model may allow early identification of mothers with a risk of not breastfeeding their babies exclusively for the first 6 months. In this way, mothers in the risk group can be closely monitored in the early period.© 2024 John Wiley & Sons Ltd.

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