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I've actually been going through this recently with a series of cancer tests with a high false positive rate. When I was discussing it with my specialist he sai
by kirrent 9y ago
I've actually been going through this recently with a series of cancer tests with a high false positive rate. When I was discussing it with my specialist he said that he and other doctors don't necessarily think of it in rigorously Bayesian terms, but they're familiar with the sensitivity and specificity of each test and have a pretty strong understanding of what that means based on priors.
Talking to medical students I get the same impression. The refrain I commonly hear is that high sensitivity tests can rule something out, and a high specificity test can rule it in. Obviously that's a reasonably shallow understanding, but when they combine that with their intuition of a prior it seems like they get pretty good results.
- turbulents 9y agoI don't think it's that they get good results, but moreso that it's the conventional wisdom (or "standard of care") and a good mechanism for learning from and properly attributing bad patient outcomes just isn't there. I doubt anybody has told them that their patient died or was given inappropriate treatments because they didn't have the proper appreciation for Bayes theorem, even if it were the root cause. That's just not the culture of medicine today.