Exactly, there’s a few specific use cases that the current generative AI is good at. Reading medical imagingand medication development are things I’d add to your list.
However, outside of those specific tasks AI is not particularly useful. An incremental improvement in productivity in some cases.
Generally speaking, yes, but standard LLMs now have their own built-in image recognition so we might not be too far off from LLMs being able to describe to the doctor what they should look at on an image that’s been flagged. Take a capable LLM of a few hundred billion parameters, train it on tons of medical images and such, and it might actually be helpful. Or it might not, no way to find out until tested.
Exactly, there’s a few specific use cases that the current generative AI is good at. Reading medical imagingand medication development are things I’d add to your list.
However, outside of those specific tasks AI is not particularly useful. An incremental improvement in productivity in some cases.
Medical imaging and medication development would be bespoke models no? Not standard LLMs?
Probably. I mis-spoke.
You can add transcription to your list though, it’s saving providers a lot of time on charting
Generally speaking, yes, but standard LLMs now have their own built-in image recognition so we might not be too far off from LLMs being able to describe to the doctor what they should look at on an image that’s been flagged. Take a capable LLM of a few hundred billion parameters, train it on tons of medical images and such, and it might actually be helpful. Or it might not, no way to find out until tested.