[mmanulis]

I'm with @greazy on this one. The assumption made is that a set of labeled images is enough. Was the training set validated against a diagnosis based on biopsy of some kind? I.e. the images that were trained on, marked by some radiologist (more likely multiple radiologists), how were they validated to contain cancer or be cancer free? Did someone follow up a few years later and confirm the diagnosis was correct?

Also, different modalities will produce different quality images, how was that accounted for in training models? Did they use all the images for a single scan or a subset of the images of a single scan?

The problem is you're trying to train a model where you have many images for a single scan, like slices. Depending on the modality, you'll get different resolutions, different "visual" inclusions, etc. etc. So labeling the individual images and labeling the entire collection is really hard.