Extended Data Fig. 3: Visual samples of distribution shifts across the medical-imaging tasks considered in this study.
From: Robust and data-efficient generalization of self-supervised machine learning for diagnostic imaging
Variation between ID and OOD data can be visually subtle or pronounced. This variation includes (but is not limited to) changes in contrast, sharpness or tint, differences in non-linear effects of X-ray-sensor construction or in zoom levels. The underlying cause of the distribution shift can be associated with technology shift, demographic shift or behavioral shift45.
