Machine learning models could enable earlier identification of at-risk children, aiding social workers and potentially improving outcomes, per Danish study of more than 100,000 children
Machine learning models could enable earlier identification of at-risk children, aiding social workers and potentially improving outcomes, per Danish study of more than 100,000 children
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Article URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0305974
Article Title: Predictive risk modeling for child maltreatment detection and enhanced decision-making: Evidence from Danish administrative data
Author Countries: Denmark, France
Funding: Funding for this project was provided by TrygFonden (TrygFondens Centre for Child Research) (https://childresearch.au.dk/en/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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Article URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0305974
Article Title: Predictive risk modeling for child maltreatment detection and enhanced decision-making: Evidence from Danish administrative data
Author Countries: Denmark, France
Funding: Funding for this project was provided by TrygFonden (TrygFondens Centre for Child Research) (https://childresearch.au.dk/en/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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