Work

Predicting successful placements for youth in child welfare with machine learning

Year: 2023

Type: article

Source: Children and Youth Services Review

DOI: 10.1016/j.childyouth.2023.107117

Authors: Kimberlee J. Trudeau, Jichen Yang, Jiaming Di, Yi Lu, David R. Kraus

Language: English

Topic: Child Welfare and Adoption

Subfield: Safety Research

Field: Social Sciences

Domain: Social Sciences

SDG: Good health and well-being

Open Access status: bronze

Funders: U.S. Department of Health and Human Services, National Institutes of Health, National Institute of Mental Health

Award: Placement Success Predictor: Using Site-Customized Machine Learning Models to Predict the Best Level of Care Placement for Each Child's Behavioral Health Needs

OpenAlex ID: W4385598012

FWCI: 3.495

Cites: 27

Cited by: 14

Related to: 10