At the moment, a big limitation of this approach is the input data. Images of tumours are generally very thin sections of a complex 3D tissue that is processed

At the moment, a big limitation of this approach is the input data. Images of tumours are generally very thin sections of a complex 3D tissue that is processed in a way that introduces artefacts and then stained with 2 colours. To truly leverage the power of machine learning, an end to end solution where the tissue is processed in a more data rich manner would be better (eg spatially aware single cell assays, non destructive thick slice imaging). This would feasibly replace the current system entirely, as it truly would do something no human could do, not just do it more accurately.