I work in this field (not directly on the ML, for the company born out of the winner of Camelyon16) and the last two years of progress has been amazing to watch. Tumor detection has become incredibly accurate, across basically every tissue/tumor type, and we're now making real progress on the next major goal: determining the best therapy for a given patient.<p>It's a bit of a dirty secret in this space that pathologists have a pretty high error rate on a lot of these tasks — it's just tough work for human eyes to do literally hundreds of times every day. Applying computer vision techniques can not only improve accuracy and reproducibility over human assessment, but you can do types of analysis in seconds-to-minutes that would literally take years for a human. We're just scratching the surface.<p>There are lots of ML challenges here, but just as many general tech/engineering/design challenges. So if you're interested in working on bringing work like this to the masses, we'd love to talk at PathAI.