Figure 1:

This figure shows 3 categories of out-of-distribution data, all in the context of training a machine-learned algorithm to read adult chest radiographs (see image C iii). A) Images that are unrelated to the task. B) Images that are incorrectly acquired. C) Images that are not encountered owing to a selection bias in the training distribution (e.g., images with lung cancer lesions and pacemakers were not included in the training set and therefore were unseen during training). C) (iii) Training data that are subject to a selection bias.