Fully autonomous medical AI is here, but are we treating it with the caution it deserves?
AI has the worst superpower… medical racism.
Medical AI can detect the racial identity of patients from x-rays. This is extremely concerning, and raises urgent questions about how we test medical AI systems.
Docs are ROCs: a simple fix for a “methodologically indefensible” practice in medical AI studies.
The way we currently report human performance systematically underestimates it, making AI look better than it is.
The FDA has approved AI-based PET/MRI “denoising”. How safe is this technology?
Super-resolution promises to be one of the most impactful medical imaging AI technologies, but only if it is safe.
This week we saw the FDA approve the first MRI super-resolution product, from the same company that received approval for a similar PET product last year. This news seems as good a reason as any to talk about the safety concerns myself and many other people have with these systems.
Improving Medical AI Safety by Addressing Hidden Stratification
Medical AI testing is unsafe, but addressing hidden stratification may be a way to prevent harm, without upending the current regulatory environment.
The best medical AI research (that you probably haven’t heard of)
I discuss a piece of medical AI research that has not received much attention, but actually did a proper clinical trial!
Half a million x-rays! First impressions of the Stanford and MIT chest x-ray datasets
My first impressions of these datasets. How do they measure up, and how useful might they be?
Medical AI Safety: Doing it wrong.
Medical AI has a safety problem; we know for a fact our testing isn't reliable. We've seen how this plays out before.
Medical AI Safety: We have a problem.
For the first time ever AI systems can directly harm patients. Are we doing enough to prevent a medical AI tragedy, the equivalent of a thalidomide event?