I am discouraged that they aren’t more widespread now. But just getting computer medical records has been a struggle. To say that a computer should be involved in the patient interview is apparently a hard thing for some people.

I bet a system like Watson will be adopted faster outside of medicine, though. The stakes are smaller, there’s fewer bureaucratic obstacles and insurance risks, and practices change faster.

MYCIN expert system was the classic and one of the earliest examples and out performed its trainers.

The main problem is that the research isn’t typically presented in the manner that a machine would need, and the problem domain is immense. MYCIN resolved this by tackling a very specific sub-domain, using a very structured knowledge base.

The approach I’ve seen used in other domains is to approach data collection in a systematic approach, and extract maximal value from a limited number of diagnostic tests. i.e. Give the same small set of tests to a large population, tabulate the results against the conditions they have, and use that set of tests on everyone to make a diagnosis.

What Watson demonstrates is the machines might be able to approach the problem in a “more human” like fashion by saying examining the medical literature in its current form.

The skills the machine will bring will include assimilation or examination of a lot of data, if we can arrange to make that data available. I’m thinking things like genetic code, and/or familial medical records. As a doctor you probably couldn’t check the medical records of all the closest living relatives of your patients for conditions which might present with the symptoms you are seeing (not did present the same way, but that could), for a system like Watson that is a trivial task for the first few thousand relatives. It can then screen them all, check if the condition is thought to be hereditary, or perhaps due to common environmental exposure, and in a couple of seconds answer the “family history” question more thoroughly than you or the patient ever could (we all know how amazingly vague people can be about their relatives conditions, and in one recent case a relative had her conditioned “misdiagnosed” and I wasn’t aware of the “update” when speaking to my own doctor). Of course that would require changes to privacy laws, or changes to practice (“Can we use your records for statistical aid in treating your relatives?”, and probably also data from stranger to set base line probabilities for certain symptoms or disorders). Realistically getting that organized isn’t going to happen (except perhaps in Sweden and similar places), and the assumption was that the “masses of data” the machine will analyse will probably be Exome or Genomic data sets and publicly available sets of related data.

Watson’s performance suggests it could also tabulate and use information from “softer” sources, like people with the same surname posting at online web forums.

I’ve long thought one of the big issues with medicine is failure to capitalize, probably because it has largely been protected from the great capitalist experiment by strict regulation. When this inevitable step takes place medicine will be revolutionized, and doctors will start scoring better than their 55% hit rate at first diagnosis.

I suspect more of the type of knowledge will be embedded in search engines, as the main way forward immediately. Google by and large has already a large proportion of that. Having out of frustration carefully constructed that Google search term describing the annoying symptoms I was experiencing at one point, and the top search result hit the nail on the head suggesting they were all due to an existing condition.

And agree with Min, the performance was stunning. Also think the speed issue is largely down to software, these kinds of difficult problems often permit of huge optimisations once you’ve learnt how to do them the hard way. Although failing that progress in hardware will probably close the gap, and it isn’t as though the big search engines and clouds are short on hardware. Indeed the curious thing about Watson is it actually stored all the data inside itself rather than going to the Internet. Imagine if you could process PubMed at 10 papers a second, you could process the most relevant papers when needed, during a 10 minute consultation you could assimilate the 6000 most relevant papers for the condition presented, following up all those citation to see if something better is being done somewhere else, or if the result in one paper was never replicated.

I also think that even if we get to where computers are comparable (or better) at pattern recognition, that we’ll be a long way from replacing human doctors with computers. There’s more to medical care than just diagnosing the patient. There’s also followup care – making sure it was the correct diagnosis. If a mistake is made, there’s also appropriate reaction to it. Some medical mistakes can kill very, very quickly, and doctors often have instincts that can react quickly enough even if they’re not entirely certain why they need to.

One of the breakthroughs with Watson’s devleopment was the realization that it needed to “hear” the other contestent’s answers, correct and incorrect, as metadata for categories. The category names are often puns of some sort that Watson didn’t understand, and only hearing correct answers from other contestents could help.

It also show how important the book digitalization projects are for google: even if they were never allowed to give direct access, they will serve as the raw data for googles “ask anything” system.

(And throw in copyright and we’ll never have Watson on our desk no matter the computional power.)

@draal Jennings know more then anyone that the IBM researcher was accurate to say this is a fair advantage though. I played quiz bowl, buzzing in is half the game.

It would help prevent missing relativly rare things.

Long term that would help drive mediacal records, and in an appropraite aggregate statistics way data mine those records, so everyone who interacts with the medical system would end out contributing to clinical results, especially for the statistics of relative frequency of conditions vs. demographics.

the current Watson computer could support 400 doctos at a time if it takes 3s to get an answer and a docotor asks once every 20 mins. It does not have to live in the same geographic location as the user.

One of the big advances is the algorithms invented to do this sort of work. As those algorithms improve or new ones are invented, less raw processing power is needed to do the same task.

Even so, the idea that within 15-20 years desktop systems could be asking “Dave, are you sure you don’t want to check your clients X levels to check for disease Y?” is just awesome.