It's worth pointing out that Vladimir Vapnik is the inventor of Support Vector Machines. The short version of what he's done here is he's come up with a way of formulating them that allows him to make use of extra information at training time (that is not available at test time).

It really is a very innovative approach IMO.

That is an important point - the extra info is only available at learning time (otherwise you need a physician sitting next to the "cancer-scanning" computer slowing down the clock speed by doing the analysis themself.) This seems obvious once you say it, but it had not occurred to me before, thanks!