Friends, can you help me think of an example of a situation in which math-based aid would help diagnosticians?

A statistical prediction rule is basically a mathematical algorithm that specifies the best tests to include in a diagnostic workup and that calculate the likelihood, based on combined results, that a condition is present.

For instance, it can be used to determine whether a person has cancer, whether a student should be admitted to law school, or whether a plane has a cracked wing. These results can either be used to decide, or to merely advise those diagnosing/deciding.

Can you think of something else a statistical prediction rule could be useful for? I need to think of one for a paper I'm writing.

Insurance companies use tables to set life insurance rates. The older you get, the more risk factors that exist (smoking, marriage, illness, etc) the more you will pay if you can buy a policy at all. It's a gamble and the insurance companies know the odds.

It would be fairly easy to apply mathematical principles to predicting the success of a marriage: health, education, prior marriages, and personality profiles could be used and it would be easy to predict the results, but love is generally blind and the odds would be meaningless to folks who think they hear bells and whistles going off.

I grew concerned about the number of accidents I saw on the freeway while driving to work in rush hour traffic. I made some calculations and determined that my wife and I stood a 50/50 chance of one of us being involved in one of those accidents in about two years. I asked my wife to swear that she would use an alternate, slower route and I did the same. Two weeks later my wife had an accident on the freeway when she was running late for work and decided to risk taking the faster route. Bummer.

If people actually used a mathematical approach to determine the hazzards of everyday life, few of us would stay in a large city like Los Angeles. Similarly, it is difficult to get smokers to quit smoking even thought the risks are obvious and predictable. It is also pretty nutty for people to buy a motorcycle in view of the fact that 90% of all motorcycle owners have an accident during the first year of riding one. We are obstinate and seldom practical about such things.

The predictability of predictions.
I've observed an unrealistic tendency to trust predictions.
As your statistical prediction is yet another foray into that field, what is the predictability of predicting?
Why should I trust that Wall Street will go up, that Real Estate investing is sound, that 'trickle down' economics will, that sports teams 'should...' etc?
Given the randomness of the universe, what accuracy has been achieved, or can be expected from predictions themselves?
Where are the Wall Street billionaires proving this point? Cite examples
The Las Vegas multimillionaires wallowing in lucre? Cite examples
The Law School students who corroborate your hypothesis, etc.
How fallacious is it to predict?

How about predicting an earthquake or other major weather condition