Application of machine learning and particularly convolutional neural networks (CNNs) to medical image diagnosis has generated as much excitement in the AI field as any use case – because of its enormous potential across the whole of healthcare. This optimism is not entirely misplaced, but as we have argued before, it is jumping the gun because a lot of basic due diligence has yet to be done, and at best these systems should be used as aids rather than for primary diagnosis at present. CNN-based analysis should be subject to more like the rigorous scrutiny applied to emerging therapies or drugs, which can take 10 years to complete from conception to full final phase clinical trial. A paper, just published…