Mitigating Bias in Radiology Machine Learning: 2. Model Development.
Radiol Artif Intell
; 4(5): e220010, 2022 Sep.
Article
em En
| MEDLINE
| ID: mdl-36204532
ABSTRACT
There are increasing concerns about the bias and fairness of artificial intelligence (AI) models as they are put into clinical practice. Among the steps for implementing machine learning tools into clinical workflow, model development is an important stage where different types of biases can occur. This report focuses on four aspects of model development where such bias may arise data augmentation, model and loss function, optimizers, and transfer learning. This report emphasizes appropriate considerations and practices that can mitigate biases in radiology AI studies. Keywords Model, Bias, Machine Learning, Deep Learning, Radiology © RSNA, 2022.
Texto completo:
1
Base de dados:
MEDLINE
Idioma:
En
Ano de publicação:
2022
Tipo de documento:
Article