[Shinkei]

I appreciate the sarcastic comment, but I don't think you understand the implication of a system like that. Even if you have more data, it doesn't better inform a patient's decision process.

For example, let's say you could--you can't--but let's say you could without a shadow of a doubt predict that the pulmonary nodule in your lung is not a cancer with 98% certainty. Well if you are 40, that's not that good actually.... that means 2 out of 100 people in a very productive time of their lives may have a cancer go completely ignored! So should I tell every patient in my report, "There is a 2% chance that this is malignant, but I won't recommend biopsy because there are chances of complications from that and we can save a lot of money by letting a few slip through the cracks--it will cost the healthcare system too much. Thanks for your understanding."

Remember, statistics predict population outcomes... not individual outcomes. I can tell someone that something very rare might happen.. but guess what, when it happens... the idea that it was a rare possibility doesn't assuage any negative feelings about it.

There is no right answer. Some people are illiterate! Even educated people don't understand statistics... how am I going to quantify that kind of risk/benefit analysis in a way that ensures a patient truly understands the implications. What if that risk were 1%, or what if the patient was 70 years old? Should either of those affect my recommendation? Who am I to decide who should be recommended one thing vs another... it's a value judgement! But if I leave it solely to the patient, a lot of times they will ask me, "What would you do?" Probably the most common thing asked after a long discussion like that. The answer is, "I don't know."

Bottom line: We can do 'strong' recommendations for things that are well studied like breast cancer and pulmonary nodules, but we don't have data to support recommendations in many other areas of everyday practice. A machine learning system would need data that just isn't available yet to make recommendations.