Definitely diseases have different challenges. Breast cancer screening being a notable outlier as far as data availabilty. For some diseases ML is probably alw

Definitely diseases have different challenges. Breast cancer screening being a notable outlier as far as data availabilty. For some diseases ML is probably always going to be problematic although may help in diagnostics mostly by helping get rid of other possibilities. I suspect we have similar overall views of the problem, but I'm pretty strongly in camp that recent advances in ML/AI are mostly really driven by data & label availability, not algorithmic advances - this colors where I think the wins to be had in medical ML can happen most easily. Either way though the non-technical barriers seem clearly higher than the technical ones still.