There are a lot of barriers to presenting it as you imagine, though: some liability, some workflow, and some just the deep lack of appropriate datasets. There is also some adoption issues - clinicians are rarely going to be happy with a black box approach but it can be difficult to explain/expose the details of such analysis in a way that clinicians will accept.
A last thought: this is actually very hard to do well and dangerous to make mistakes with - so your rather cavalier claim that there would be immediate and wide spread improvement of health care should be tempered a bit.
Another thing to consider in any work like this, you really need to thank about what your false positives mean, in a practical sense. If your numbers are big enough (e.g. screening) and your positives result in a procedure (e.g. biopsy), eventually someone is going to die based on a false positive. This may still be the better option, of course, but you really need to demonstrate that, and think about what your sensitivity and specificity tuning needs.
Going back further, medical diagnosis was a classic application of expert systems even in the 1970s. They ended up being something of a failure then due to the need to laboriously extract huge amounts of knowledge from doctors to get them to work, but it does show that it's long been a popular idea in the field.
MYCIN was never actually used in practice but research indicated that it proposed an acceptable therapy in about 69% of cases, which was better than the performance of infectious disease experts who were judged using the same criteria. [...] Some observers raised ethical and legal issues related to the use of computers in medicine — if a program gives the wrong diagnosis or recommends the wrong therapy, who should be held responsible? However, the greatest problem, and the reason that MYCIN was not used in routine practice, was the state of technologies for system integration, especially at the time it was developed. MYCIN was a stand-alone system that required a user to enter all relevant information about a patient by typing in responses to questions MYCIN posed. The program ran on a large time-shared system, available over the early Internet (ARPANet), before personal computers were developed. In the modern era, such a system would be integrated with medical record systems, would extract answers to questions from patient databases, and would be much less dependent on physician entry of information. In the 1970s, a session with MYCIN could easily consume 30 minutes or more — an unrealistic time commitment for a busy clinician.
Given that the systems integration problems should be soluble now, if not already solved, it does seem a little surprising that there isn't a modern version of such a thing, far more sophisticated, in general use. I guess the ethics and liability problems still loom larger than the above quote suggests.
[0] https://en.wikipedia.org/wiki/Mycin
[1] http://people.dbmi.columbia.edu/~ehs7001/Buchanan-Shortliffe...
Also such system is quite complex in many dimensions, so the natural risk minimization strategy would be to introduce it in stages: a system that warns about drug interactions here, monitors drug dosage there, reminds you to order extra tests, etc .And of course everything needs to be clinically tested to be accepted by docs(even though it isn't stricly necessary, it's just a second opinion, reminders, not the final word) . It makes for a very slow process.
And they they all face very big adoption barriers , in some cases upto 96% of their recommendations are skipped. Some of this is due to usability , but a lot due social/political factors.
Now after seeing this, what company in it's right mind will invest in developing a full diagnostical system ?
Actually , i know of one who did, http://www.isabelhealthcare.com , but at least according to the founding story , it began because the founder nearly lost his daughter to a hospital misdiagnosis, so he wasn't really driven by money.
And as far as i know(haven't followed them in a long time), they only achieved small scale sucsess.
The other company now entering this is IBM , but that's a bit of a unique case: IBM may be in big trouble so they take a huge bet, and the field they choose - cancer , is such that patients have much more power than usual , a patient has time, and can demand a diagnosis by Watson , heck it's even a cloud service, you just need to send blood and pay.
What's more, its definitely open to the public, except it isn't really promoted at all (it's only open in the interests of openness, you're not really meant to use it.) As such I can't find the URL for the life of me. Perhaps they closed it.
Any doctor or nurse will know about it, perhaps someone can post the link.
Lots, and for decades. If you Google "AI medical diagnosis" you get a zillion hits, including a dedicated Wikipedia page.
Something like this would be immensely valuable, and would immediately improve healthcare everywhere, since the software could be updated with new or obscure knowledge right away, so you wouldn't have to shop around for doctors until you came across someone who had read of a very rare disease somewhere, the software would already know everything you might have.
Is there something like that out there? It sounds like there must be, but I don't know of any doctors using anything like this.