Exploring Machine Learning to Support Decision-Making for Placement Stabilization and Preservation in Child Welfare.

The Family First Prevention Services Act requires youth's placement in residential care to be clinically appropriate, time-limited, and only when youth's needs cannot be met in family-like settings in foster care. State child welfare agencies can benefit from upstream, empirical decision support to...

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Publicado en:	Journal of Child & Family Studies Vol. 34; no. 1; pp. 282 - 298
Autores principales:	Chor, Ka Ho Brian, Luo, Zhidi, Rodolfa, Kit T., Ghani, Rayid
Formato:	Artículo
Publicado:	Springer Nature Jan2025
Materias:	Child welfare Foster home care Health planning Health care rationing Random forest algorithms Prediction models Research funding Logistic regression analysis Decision making in clinical medicine Descriptive statistics Machine learning Decision trees Residential care Regression analysis
Acceso en línea:	Ver este registro en EBSCOhost