Gender Bias in Artificial Intelligence: Severity Prediction at an Early Stage of COVID-19
Artificial intelligence (AI) technologies have been applied in various medical domains to predict patient outcomes with high accuracy. As AI becomes more widely adopted, the problem of model bias is increasingly apparent. In this study, we investigate the model bias that can occur when training a mo...
Guardado en:
Autores principales: | Heewon Chung, Chul Park, Wu Seong Kang, Jinseok Lee |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/5504b15f398e44e289120b0e28e27089 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Artificial Intelligence, Heuristic Biases, and the Optimization of Health Outcomes: Cautionary Optimism
por: Michael Feehan, et al.
Publicado: (2021) -
Reply to Letter to the Editor on “Not all biases are bad: equitable and inequitable biases in machine learning and radiology”
por: Mirjam Pot, et al.
Publicado: (2021) -
Sources of bias in genetic association studies of cattle: a review
por: José L. Zepeda Batista, et al.
Publicado: (2018) -
Sex and Gender Bias in Covid-19 Clinical Case Reports
por: Aysha E. Salter-Volz, et al.
Publicado: (2021) -
Modeling, Quantifying and Visualizing Media Bias on Twitter
por: Anam Zahid, et al.
Publicado: (2020)