I think it is good to remain skeptical about medical ML, but I don't think it should be because of the algorithms or that retrospective analysis is flawed. In most retrospective medical research, the data sizes are relatively small. Likewise current ML needs huge amounts of labeled data to be accurate, and patient data just isn't available to ML experts in the volumes necessary. The question I have is would dramatically increasing the size of available patient data improve ML analysis? Is it the case that some of the flaws of retrospective analysis are actually a result of too little data especially in the context of ML? I don't know the answer, but I do know we need to fix the data availability problem if we want to find out. How do we fix the data availability problem? Not sure either, it a complex problem.