|
|
|
|
|
|
by Thebroser
1955 days ago
|
|
|
Maybe not hard data, but EPIC's software (which is used in about ~25% of hospitals for EHR) has over the years been utilizing patient data to be used for treatment recommendation purposes. Again, difficult to weigh the impact if we don't know how many doctors are relying on these types of recommendations and acting on them but it is definitely out there in the real world at the moment. >>https://www.epic.com/software#AI |
|
|
I can answer that: close to zero. Clinicians don't want stuff that makes recommendations, as good as they may be. They want a bycicle for the mind: something that helps them visualize, understand the big picture and anticipate better. And also ensure that trivial stuff to do is not forgotten (now that's the place a recommender engine could fit in). That's a fundamental misunderstanding of what a clinician's job is that is unfortunately very common.
What do you ask of your software tooling? Do you want something that just tells you what to write? No, you want a flexible debugger. A compiler with precise error messages. You want a profiler with a zillion detailed charts allowing you to understand how everything fits together and why such and such is not the way you anticipated. Same thing for medicine until the day machines will actually do better than humans, which is not tomorrow nor the day after.