Shouldn't A.I. not be used in a way that it only tries to assist? E.g. a doctor takes a look first and if (s)he can't find anything then A.I. is checking as well (or in parallel).
There is other comment very correctly noting that this result is on 100% positive input. Same AI in “real life” would score probably much better eventually. But as you point out, if used as a confirmation tool, is definitely bad.
Either I don't understand your reasoning or you are very much wrong. A "real life" dataset would contain real negatives too and the result would be equal if false positive rate was zero and strictly worse if the rate was any higher. One should expect the same AI to score significantly worse in a real life setting.
What I mean with “score” is having a relatively high accuracy.
Come let’s do the math: incidence of BC is 1 every 12, lets say. Now let’s say we have 12000 patients:
Acuracy = (TP + TN) / (TP + TN + FP + FN) = (1000 + 11000) / (1000 + 11000 + 300 + 0) = 12000 / 12300 =0.976 the test is 97.6% accurate… pretty impressive huh?
Tell me if I’m wrong. Is a know fact that you have to be careful when doctor speak of % accuracy.
There's a roundup of such findings here, but they're a mixed bag: https://www.uxtigers.com/post/humans-negative-value I suspect you need careful process design to get better outcomes, and it's not one-size-fits-all.