Drop the shortcuts: image augmentation improves fairness and decreases AI detection of race and other demographics from medical imagesResearch in context

Drop the shortcuts: image augmentation improves fairness and decreases AI detection of race and other demographics from medical imagesResearch in context

Summary: Background: It has been shown that AI models can learn race on medical images, leading to algorithmic bias. Our aim in this study was to enhance the fairness of medical image models by eliminating bias related to race, age, and sex. We hypothesise models may be learning demographics via sh...

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Bibliographic Details
Main Authors: Ryan Wang, Po-Chih Kuo, Li-Ching Chen, Kenneth Patrick Seastedt, Judy Wawira Gichoya, Leo Anthony Celi
Format: Article
Language:English
Published: Elsevier 2024-04-01
Series:EBioMedicine
Subjects:
Bias mitigation
Shortcuts
Augmentation
Fairness
Deep learning
Online Access:http://www.sciencedirect.com/science/article/pii/S2352396424000823

Internet

http://www.sciencedirect.com/science/article/pii/S2352396424000823

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