Oh yes it is. I have worked on projects where highly trained specialized doctors have helped train the models (or trained them themselves) to catch random very difficult to notice conditions via radiology. Some of these systems are deployed at different hospitals and medical facilities around the country. The radiologist still does there job, but some odd, random hard to notice conditions, AI is a literal life saver. For example, pancreas divisum, a abnormality in the way the pancreas ducts fail to fuse/etc can cause all kinds of insane issues. But its not something most people know about or look for. AI can pick that up in a second. It can then alert the radiologist of an abnormality and they can then verify. It's enhacing the capabilties of radiologists.
> Some of these systems are deployed at different hospitals and medical facilities around the country. The radiologist still does there job, but some odd, random hard to notice conditions, AI is a literal life saver
I would be very interested if you could provide specific examples.
>Oh yes it is.
>It's enhacing the capabilties of radiologists.
So it is not replacing radiologists?
I guess we have to define 'replace' then. If we need fewer radiologists, does that count as replacing? IDK.
It seems that with AI in particular, many operate with 0/1 thinking in that it can only be useless or take over the world with nothing in between.
Not yet. Time will tell but they have a long way to go if they ever do. They are useful tools now.
what's the end game here, have a slew of of finetuned models for these varying edgecases?