S1 Syntax - Application of machine learning algorithms to predict early childhood development in children aged 24–59 months across three East African countries

S1 Syntax - Application of machine learning algorithms to predict early childhood development in children aged 24–59 months across three East African countries

S1 Syntax - <p>Application of machine learning algorithms to predict early childhood development in children aged 24–59 months across three East African countries</p>

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Bibliographic Details
Main Author:	Tsion Mulat Tebeje (13955254) (author)
Other Authors:	Solomon Hailemariam Tesfaye (15420410) (author), Gizaw Sisay (13510161) (author), Binyam Tariku Seboka (10021426) (author), Getanew Aschalew Tesfa (11775408) (author), Daniel Sisay (12432844) (author), Mesfin Abebe (12400154) (author)
Published:	2025
Subjects:	Medicine Genetics Biotechnology Developmental Biology Science Policy Infectious Diseases Biological Sciences not elsewhere classified women &# 8217 similar socioeconomic contexts improve parenting practices extreme gradient boosting prioritize preprimary education least secondary education best performing models machine learning algorithms xlink "> data maternal education level evaluated using area machine learning model xlink "> population level best algorithm whose mothers top three testing sets randomly divided random forest psychosocial well predictive ability overall development modest majority lifelong outcomes future development equitable access ensemble model empower mothers effective tool east africa developmental outcomes crucial role classification metrics child age beeswarm plot 71 %. 59 months 35 months
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Summary:	S1 Syntax - <p>Application of machine learning algorithms to predict early childhood development in children aged 24–59 months across three East African countries</p>

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