Anecdotal, but I had a suspicious mole looked at, the doctor couldn't decide, got a second opinion from their colleague, he still was only 90% sure. And that's a relatively simple example. Doctors are some of the smartest/hard working people in society, and if they can still make mistakes, medical-grade AI is a long way off.
The benefit of medical-grade "AI" (in particular, multi-layered convolution neural networks) is that, given an aggregate of information (say, if you equipped every derm and oncologist with high resolution cameras and a set of parameters to standardize each datum), a trained professional[1] would be able to use that corpus as a very useful resource (used, obviously, in conjunction with their formal training and years of medical experience).
That being said - this is a question you should really be asking those who practice medicine or are actively in research for a living. Go pick up the last years issues of Nature Methods to see what problems they're encountering, and which technological gaps[2] (if any) they may have where YC AI might be applicable.
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[1] Needless to say, this is something I'd be very reluctant to release into the populace's hands, lest you have someone whip together some node.js backend and React iOS app :: "Do I have Skin Cancer? $10 to find out!". One shudders to think what sort of hysteria might follow.
[2] You would be surprised at how technologically adept some of the members of those research teams are -- within a month of DeepMind making the headlines on our tech blogosphere, I was seeing RNN being applied to their industry.
I've had this discussion with my SO (who is a doctor) many times, she strongly believes the breadth+depth of knowledge required for such an AI would be too great, but perhaps as a tool for GPs, or for specific, easy ailments (i.e. telling a patient what they don't have, and if it's serious enough to raise the issue to an actual doctor).
IBM's Watson at MD Anderson Cancer center did not work out real well for them. In other words, using AI in the realm of medical diagnostics is very difficult.
Overall, of course, you're right. Liability is the problem with my suggestion. Doctors prescribe to treat, they also prescribe to meet the legally mandated standard of care and minimize second-guessing later. Looking at each patient as a unique snowflake-- or at least, part of a thinner-sliced group-- helps with the first, but directly undercuts the second goal. Such an approach would probably need to originate outside the U.S.
Extracting data from the EMR is very difficult because all EMR was originally intended to only be a storage place for data - not designed to output data back to a user.
Say a user decides to self-diagnose and damages themselves (either through inaction or self-medication or whatever). What difference does it make whether they diagnosed themselves by browsing symptoms on wikipedia or using an advanced diagnosis AI on their phone?
Why do you want to have the diagnosis before seeing a physician? (I'm legitimately interested in the answer.)
In my experience, it's about 50-50 with helping versus hurting making the correct diagnosis and providing accurate treatment.
Even in the US where you actually have to pay for medical stuff, it can't be more than $10 or so for a quick consultation?
You also have no idea of the cost of various diagnostic actions they might take. I once had blood drawn and got charged $600 for it because the lab they chose was out of network. I didn't even know there was a cost, let alone which labs to request.
Or you could see it this way :
$150 to have a nurse put a popsicle stick on your tongue and tell you that you are very lucky to have presented today because you have a suspicious growth - which on examination turns out to be a rare form of cancer that is easily cured if detected early, but most certainly fatal otherwise
It's times like this I realize just how different the rest of the world is.
We can learn a lot from animals, and clearly the data should not be protected as much as for humans. Therefore, I'm wondering, where is all the animal data? Could we already start to build models using that data? This could be useful for researching conditions that are more difficult to get data for in the case of humans.
I foresee in less than ten years we will have a doctor in our pockets. No, it won't cure us and it won't replace a doctor, but it will give us all the information we need to have a 99% certainty of our condition.
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Second batch for animals and their conditions.
Third batch, agriculture. Take a pic of a plant and tell me all the info, fertilizers, cultivation, etc, bonus for pest id and treatment.
Pocket computers should be able to diagnose every living creature.