Doctors make errors all the time though, so the real argument is about the error percentage. If AIs is lower then it's safer (but it's hard to have that convo, I recognise).
Besides; this article was about diagnosis not prescribing. It's pretty obvious, I think, that diagnosis is one area where AI will perform extremely well in the long run.
I think there are two metrics; the first is outright misdiagnosis, which studies put between 5 and 8% in US/Europe. That's a meaningful number to tackle.
Secondly; overdiagnosis. Where a Dr says on balance it could be X on a difficult to diagnose but dangerous problem (usually cancer). The impact of overdiagnosis is significant in terms of resources, mental health, cost etc.
Do you believe the issue is because they don't have enough technicians to diagnose or because they don't have enough x-ray machines?
Or in a ER environment, how an AI would speed up things in a real way that improves patients' lives?
We just minted the term "cognitive debt" for software engineers that cannot keep up with what the AI spits out. How would that apply to ER doctors, or any other kind of doctor?
I'm not talking in particular about the X rays. It's about general lack of hospitals, equipment and doctors.
In Europe, there are some rich cities which have on average one doctor per hundred people. And there are large areas in Eastern Europe that have ten times less than that.
If you have some unusual symptoms or a little pain somewhere and no access to doctors you will most likely ignore it.
If you can get any diagnosis it can help you e.g. decide to travel to get treatment.
And the locally available alternative for ai diagnosis is a doctor you can get to in few months, who works 80 hours a week and has 10 minutes per patient.
For ai to be valuable you really don't need to be better than average physician in top American clinic.
I agree with you, but seperate point in many respects - the conversation was about replacing existing robust medical infrastructure.
I fully agree that AI could extend access; but to build on what others have said too, lack of physical diagnostics is an issue as is the lack of physical tech infrastructure.
Besides; this article was about diagnosis not prescribing. It's pretty obvious, I think, that diagnosis is one area where AI will perform extremely well in the long run.
I think there are two metrics; the first is outright misdiagnosis, which studies put between 5 and 8% in US/Europe. That's a meaningful number to tackle.
Secondly; overdiagnosis. Where a Dr says on balance it could be X on a difficult to diagnose but dangerous problem (usually cancer). The impact of overdiagnosis is significant in terms of resources, mental health, cost etc.