I think better diagnostic testing is one way to solve this. Oncology in some ways is easy since the data input is usually a set of biomarkers particular to that tumour (i.e. estrogen receptor, her2/neu, etc). It's probably the most rapidly advancing field in medicine. Same with radiology and dermatology where the input can be images which can be standardized. Dealing with analog humans is another challenge entirely!

Better biomarkers for acute illnesses with fewer false positives would help you better test 'accuracy' versus an ML model.