A lot of machine learning people don't really understand study design or power or things like that. It's gotten a little better over the past decade or so, but this is an area where the field has a lot of room to improve.
I could agree with your claim if you meant bootcamp programs or data science sorts of coursework, but machine learning is generally grounded in both measure theoretic probability theory and a robust understanding of applied statistics before moving on. After that will be the basics of pattern classification, clustering, regression and dimensionality reduction. Last of all will be very domain-specific tools for NLP, computer vision, audio processing involving e.g. deep neural networks.
Clinical research that isn’t making ridiculous claims tends to get much less press.
Furthermore, of all places to lap that crap up... this hacker news site is frankly one of the worst.
I mean look at this submission. Yes it’s true people are pillorying it here (including some doctors), but i don’t recall much interesting well designed medical research being discussed here (though arguably maybe not the place for it)