Aug 5, 2024 · In this paper we investigate the source of this bias, seeking to understand its root cause(s) so that it can be effectively mitigated.

We show that the main source of bias is in the image content outside of the heart region and that bias can be reduced by cropping the images before training ...

The paper investigates race bias in AI-based cardiac magnetic resonance (CMR) segmentation models, focusing on the source of bias, the extent of ...

Aug 8, 2024 · In the classification experiments, we found that race can be predicted with high accuracy from the images alone, but less accurately from ground ...

Aug 5, 2024 · This paper investigates the causes of race bias in AI-based cardiac magnetic resonance (CMR) image segmentation, a critical issue that can have significant ...

Artificial intelligence (AI) methods are being used increasingly for the automated segmentation of cine cardiac magnetic resonance (CMR) imaging.

We have shown that racial bias can exist in DL-based cine CMR segmentation models when training with a database that is sex-balanced but not race-balanced such ...

We investigate the impact of model choice on how imbalances in subject sex and race in training datasets affect AI-based cine cardiac magnetic resonance image ...

This work investigates the impact of model choice on how imbalances in subject sex and race in training datasets affect AI-based cine cardiac magnetic ...

We investigate the impact of model choice on how imbalances in subject sex and race in training datasets affect AI-based cine cardiac magnetic resonance image ...