This reminds me of those 20 Questions apps. Have you tried a good one lately? "Akinator" on iOS has an incredible ability to predict the person or character you're thinking of. It successfully guessed "one of the twins from The Shining" and "Calvin's dad from Calvin & Hobbes" when I played.
I can't imagine there are more possible diagnoses than there are fictional characters and famous people.
Getting the right answer in 20 questions actually relies on a rough implementation of binary search over a huge possible "thing space". A problem I can see with applying this to medicine is that medical conditions don't always present in the same way and measurable factors are not binary, so you often can't rule out a hypothesis with a certain result, even if it reduces the probability of that hypothesis.
The decision algorithm in the article is amazing in its accuracy and simplicity. There is probably some other low-hanging fruit in reproducing this method in other areas of medicine by working with someone who already has a high degree of accuracy in their diagnoses, but doesn't fully understand their own process. But outside of areas where anyone has the current ability to make such accurate diagnoses, it would be a lot more complicated.
You'd need to determine which factors are important, which of those are covariant, and how that relationship works. Then from there, work over tons of data to establish a bayesian model with weightings to apply to each factor so that you can observe the evidence, plug it into the model, and get out your probability distribution over possible diagnoses. It's no easy task, but I believe that this kind of approach is the future of medicine.
Pretty cool. I beat it with 'Jane Whitefield' and was only the second person to play 'Jim Chee' (24 questions). I think it's a learning program since it asked me to choose the answer when it lost.
I can't imagine there are more possible diagnoses than there are fictional characters and famous people.