Developing machine learning-based models to help identify child abuse and neglect: key ethical challenges and recommended solutions

Landau, A. Y., Ferrarello, S., Blanchard, A., Cato, K., Atkins, N., Salazar, S., Patton, D. U., & Topaz, M. (2022). Developing machine learning-based models to help identify child abuse and neglect: key ethical challenges and recommended solutions. Journal of the American Medical Informatics Association, 29(3), 576–580. https://doi.org/10.1093/jamia/ocab286
Authors:
Aviv Y. Landau
Susi Ferrarello
Ashley Blanchard
Kenrick Cato
Nia Atkins
Stephanie Salazar
Desmond U. Patton
Maxim Topaz
Affiliated Authors:
Aviv Y. Landau
Ashley Blanchard
Kenrick Cato
Nia Atkins
Maxim Topaz
Columbia Affiliation:
Subjects:
Child Abuse (MeSH)
Author Keywords:
child abuse and neglect
phenomenological ethics
machine learning-based risk models
pediatric emergency departments
electronic health records
machine learning–based risk models
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Publication Type:
Article
Unique ID:
10.1093/jamia/ocab286
PMID:
35024859
DOI:
10.1093/jamia/ocab286
Journal:
Journal of the American Medical Informatics Association
Publication Date:
Data Source:
Scopus
Source Link:
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