The Untapped Potential of Nursing and Allied Health Data for Improved Representation of Social Determinants of Health and Intersectionality in Artificial Intelligence Applications: A Rapid Review

Ronquillo, C. E., Mitchell, J., Alhuwail, D., Peltonen, L.-M., Topaz, M., & Block, L. J. (2022). The Untapped Potential of Nursing and Allied Health Data for Improved Representation of Social Determinants of Health and Intersectionality in Artificial Intelligence Applications: A Rapid Review. Yearbook of Medical Informatics, 31(01), 094–099. CLOCKSS. https://doi.org/10.1055/s-0042-1742504
Authors:
Charlene Esteban Ronquillo
James Mitchell
Dari Alhuwail
Laura-Maria Peltonen
Maxim Topaz
Lorraine J. Block
Affiliated Authors:
Maxim Topaz
Columbia Affiliation:
Subjects:
Artificial Intelligence (MeSH)
Medical Informatics (MeSH)
Author Keywords:
artificial intelligence
health equity
health personnel
informatics
social determinants of health
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Publication Type:
Article
Unique ID:
10.1055/s-0042-1742504
PMID:
35654435
DOI:
10.1055/s-0042-1742504
Journal:
Yearbook of Medical Informatics
Publication Date:
Data Source:
Scopus
Source Link:
View Scopus Record
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