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this post was submitted on 03 Apr 2026
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I can't wait for this bubble to blow up in all their dumb faces.
For what it’s worth, “AI” in this context is probably not the content-stealing Generative AI that everyone is trying to cram everywhere it doesn’t belong. This is a much more legitimate application of a similar technology.
I’m not mad about the idea of AI in radiology because it’s a really good fit. A human radiologist can’t compare a hundred similar slices and cross-correlate possible anomalies, whereas AI can. This improves detection and outcomes and is exactly where medical technology is supposed to help.
That said, I don’t think we’ll replace radiologists across the board for a long time. This will be a very useful tool and will probably reduce the number of radiologists required and modify their roles significantly, but it’ll be more like how a single worker with editing software can do work that would have required a small team in the pre-digital days of film.
Yeah, it sounds more like ML. That's a good thing, For one thing, it's reproducible.
LLMs are intrinsically unfit for use in any situation where human life or health is at stake.
Exactly. People keep shoehorning Large Language Models into non-linguistic domains, and that’s dangerous. Human language, with respect to the training sets used, is inherently subjective and imperfect. Healthcare is very fault-intolerant.
The replacing part is the problem. Using a local system to help is fine, but it still requires humans who know what they're doing and what they're looking at.
Sometimes, for example human + AI systems used to be better than either one in isolation, but chess AI improved so much that the human partner is actually not helping anymore
But chess is an isolated "system" with clear rules. Reality and especially medicine is so much more complicated.
If it's done properly, sure.
Last time this was in the news, they found that AI had an insanely good accuracy at identifying cancer! Until they realized it was because they included the hospital info in the training data, so it was identifying "cancer" by seeing they were at a cancer treatment facility.