The diabetic retinopathy study (and the somewhat recent stanford dermatology study) were the first ML studies I had read about that blew me away in terms of their sensitivities and specificities, as compared to real doctors. Your comment on specific subtasks is perfect, and I try and use these examples when discussing ML with fellow medical students.
However, like you said, the medical field is very slow, and has quite a lot of inertia to maintain the status quo. Unless insurance companies refuse to compensate practitioners that don't use these tools, I fear that few, if any, in the healthcare field will opt to use such techniques.
And finally: How should someone with both a medical and computer science background get into ML?
However, like you said, the medical field is very slow, and has quite a lot of inertia to maintain the status quo. Unless insurance companies refuse to compensate practitioners that don't use these tools, I fear that few, if any, in the healthcare field will opt to use such techniques.
And finally: How should someone with both a medical and computer science background get into ML?