Cargando…
Racial Equity in Healthcare Machine Learning: Illustrating Bias in Models With Minimal Bias Mitigation
Background and objective While the potential of machine learning (ML) in healthcare to positively impact human health continues to grow, the potential for inequity in these methods must be assessed. In this study, we aimed to evaluate the presence of racial bias when five of the most common ML algor...
Autores principales: | Barton, Michael, Hamza, Mahmoud, Guevel, Borna |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cureus
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10023594/ https://www.ncbi.nlm.nih.gov/pubmed/36942183 http://dx.doi.org/10.7759/cureus.35037 |
Ejemplares similares
-
Evaluation and Mitigation of Racial Bias in Clinical Machine Learning Models: Scoping Review
por: Huang, Jonathan, et al.
Publicado: (2022) -
Connections and Biases in Health Equity and Culture Research: A Semantic Network Analysis
por: Martínez-García, Mireya, et al.
Publicado: (2022) -
Mitigating bias in machine learning for medicine
por: Vokinger, Kerstin N., et al.
Publicado: (2021) -
Implicit Bias and Patient Care: Mitigating Bias, Preventing Harm
por: Barber Doucet, Hannah, et al.
Publicado: (2023) -
Racial underrepresentation in dermatological datasets leads to biased machine learning models and inequitable healthcare
por: Kleinberg, Giona, et al.
Publicado: (2022)