News Release

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

Peer-Reviewed Publication

PLOS

Predictive risk modeling for child maltreatment detection and enhanced decision-making: Evidence from Danish administrative data

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Machine learning models could enable earlier identification of at-risk children, aiding social workers and potentially improving outcomes.

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Credit: Nathan Dumlao, Unsplash, CC0 (https://creativecommons.org/publicdomain/zero/1.0/)

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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