Some kind of machine/human integrated medical system is a common goal of current research. Where many AI people think the lack of uptake is coming from, besides just general resistance to AI diagnosis, is that current systems don't have great real-world usability.
A few issues: There is a lot of information available to the doctor in a typical diagnostic setting that is not currently codified in machine-readable form, and asking the doctor to do custom data entry per patient is not likely to improve uptake. Ideally the systems should integrate with other patient-information-management systems, and such patient-information systems might need to be augmented with new or differently coded data collection. Perhaps equally or more importantly, if the AI system is going to be a component of the diagnosis rather than handed over full trust to make the diagnosis, it should ideally produce "white-box" diagnoses with justification for its reasoning and human-readable explanation of what it thinks the situation is, not just black-box predictions.
