Addressing racial disparities in surgical care with machine learning.
Journal
NPJ digital medicine
ISSN: 2398-6352
Titre abrégé: NPJ Digit Med
Pays: England
ID NLM: 101731738
Informations de publication
Date de publication:
30 Sep 2022
30 Sep 2022
Historique:
received:
07
06
2022
accepted:
12
09
2022
entrez:
30
9
2022
pubmed:
1
10
2022
medline:
1
10
2022
Statut:
epublish
Résumé
There is ample evidence to demonstrate that discrimination against several population subgroups interferes with their ability to receive optimal surgical care. This bias can take many forms, including limited access to medical services, poor quality of care, and inadequate insurance coverage. While such inequalities will require numerous cultural, ethical, and sociological solutions, artificial intelligence-based algorithms may help address the problem by detecting bias in the data sets currently being used to make medical decisions. However, such AI-based solutions are only in early development. The purpose of this commentary is to serve as a call to action to encourage investigators and funding agencies to invest in the development of these digital tools.
Identifiants
pubmed: 36180724
doi: 10.1038/s41746-022-00695-6
pii: 10.1038/s41746-022-00695-6
pmc: PMC9525720
doi:
Types de publication
Journal Article
Review
Langues
eng
Pagination
152Informations de copyright
© 2022. The Author(s).
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