[dekhn]

This is an incredibly important point. Medical research must be taken seriously and I see many problems with the processes being applied here.

(for those who care- I'm a published ml biologist who works for a pharma that develops human health products. Having worked in this area for some time, I often see people who have no real idea of how the medical establishment works, or how diagnostics are marketed/sold/regulated. Overconfidence by naive individuals can have massive negative outcomes.

[w1nk]

Why does everyone assume this guy has zero business attempting this? If you read his credentials, he should be every bit as qualified as you to attempt this kind of work while understanding the pitfalls.

According to his CV he's been active in the field for quite some time. The default assumption that he's an idiot and going to kill people just seems too cynical here.

Grandparent - you specifically mention having noted methodology problems, would you mind sharing where in the methodology you think he's gone wrong?

[tfgg]

I'm not going to detail challenges in medical ML - the literature can do that. But just to mention one that other people haven't that goes beyond just precision-recall: algorithms can be biased based on variance in physiology (e.g. more accurate for men), and understanding how an algorithm is biased is very important for the person interpeting the information, who should be a trained doctor.

And it doesn't matter what his credentials are, that's appeal to authority. If he thinks this should be used and trusted by people for decision making, then he should submit it to independent peer review and regulatory approval.