Where, why, and how is bias learned in medical image analysis models? A study of bias encoding within convolutional networks using synthetic data.
Journal:
EBioMedicine
Published Date:
Dec 12, 2024
Abstract
BACKGROUND: Understanding the mechanisms of algorithmic bias is highly challenging due to the complexity and uncertainty of how various unknown sources of bias impact deep learning models trained with medical images. This study aims to bridge this knowledge gap by studying where, why, and how biases from medical images are encoded in these models.