Wait until you have a rare disease before you say something like you want AI help diagnose you (or make decisions about your healthcare for that matter—the US is going to be a mess if they go this route). 7% of the general population collectively has a rare disease, so it’s not uncommon to have a rare disease. Most of them are classified as very rare.

I personally have 2 rare diseases affecting my peripheral nervous system, and one of them is very rare. The very rare disease is believed to have also caused my type 1 diabetes.

The wild part? The very rare disease, which I had prior to my type 1 diabetes diagnosis, which was also undiagnosed at the time, was blamed as “type 1 diabetes related complications” specifically autonomic neuropathy by human doctors.

Do you think AI would get this right? The answer is an obvious no.

Also, I am in my early 30s. My endocrinologist was surprised that I was 30 and was making a big deal about it (as in “you survived and you shouldn’t be alive” sense). It was never statistically likely that I would be alive, which is why AI should never be used.

So do you think AI should be making health decisions in a healthcare system that already has a ton of human error, and is trained on those errors?

I mean, the third leading cause of death in the US is believed to be preventable medical errors: https://www.bmj.com/content/353/bmj.i2139

I don't understand your argument.

You're saying that humans are unacceptably bad. Then why is it a problem to replace them with also unacceptably bad AI. Like, either way you're not getting the treatment you need.

At least if the AI fails you, then nobody is going to get their ego stepped on if you go to get a second opinion. Whereas with a doctor you have to go through a few uncomfortable conversations and then hope that the next guy isn't going to ignore you because they don't want to sour their relationship with your first doctor.

> Do you think AI would get this right? The answer is an obvious no.

Today? Sure. But really one of the most plausible ways in which AI could be more effective than human clinicians is in rare diseases. It assumes a massive input of data of course, but clinicians are biased against this in ways that are hard to do anything effective against. This is why so many people with rare conditions spend years before getting a proper diagnosis.

Getting that data is an extremely hard problem. In general the data is low quality, incomplete, poorly coded, and full of errors. Cleansing the data to the point where it could be used to train a useful decision support algorithm would require a tremendous amount of human labor by expert clinicians. This isn't something that can be automated.

Okay ... how do doctors (individually or as a whole) get better at doctoring? Either we're saying they look over the data OR we're saying that they somehow just mystically know better as time goes on.

Who cares if it turns out that we can't automate the formation of the AI. But we're doing the same work to continually educate and improve doctors already. At least with the AI it won't die of old age once it starts to get really good at what it's doing.

And maybe it turns out that the best that AI can do is duplicate a middle level doctor who isn't really interested in self improvement. If that's the case then at least everyone can get cheap and fast health care that's the same frustrating quality that we're stuck with now. Only with the AI you can say that it's dumb and everyone will believe you. With a doctor you have to fight past "impugning the reputation of the profession" in order to get a real diagnosis.

Doctors are getting better at doctoring mostly through simple things like checklists and evidence-based medicine treatment guidelines. Those reduce variance and the risk of error. Improved interoperability between clinical systems also has potential to reduce errors by making sure all members of a patient's care team have complete access to the patient's entire record.

Diagnosis isn't particularly difficult or time consuming in most routine cases after gathering the necessary data. If you see a jagged line on the x-ray then the patient has a fractured bone. If the A1c level is 7.5% then the patient has diabetes. Etc. Improving diagnostic accuracy will help in rare cases and is worth doing, but that won't have much impact on the health care system as a whole.

I don't think I understand your argument.

You at first appear to say that gathering data and automating things is hard and might not be possible.

Then here you're saying that checklists, evidence-based guidelines, and improved interoperability between systems are all the source of doctor improvements.

These are all arguably forms of AI that have been created through data gathering. Yes, a checklist is a very boring AI, but it's taking some knowledge out of the heads of a group of people and then making it available for someone else to use. The missing step seems to be that instead of having a person look at a piece of paper and execute the checklist and evidenced based treatment, having a computer do it.

You're missing the point. There's no cost effective way to provide the computer with the complete, high quality data necessary to execute the checklists.

I hope I can be forgiven for missing the point when this is the first time (as far as I can tell ... perhaps you said something in a different thread) you've mentioned cost. At first it was "this cannot be automated". Then it was "well it happened, but it's okay because it's written down on paper and not put in a computer".

Now we're talking about cost. Cost where (at least in the USA) going to the ER for a broken bone can cost thousands of dollars. Cost where (at least in the USA) a birth (something people from all walks of life go through) has a minimum of the patient spending $10K and regularly gets into the $50K and up range (not even talking about ultrasounds etc leading into the birth).

I cannot believe that we're really talking about data collection being too expensive for the medical industry. Maybe nobody wants to be the person to pick up the bill. But it's going to be a rounding error of a rounding error compared to all the other money that goes through that industry.

The data gathering and entry can't be automated. It could be done manually, but at a very high cost (not a rounding error). Commercial insurers and Medicare certainly wouldn't be willing to pay. As a practical matter it's just not worth doing in the vast majority of cases.

Thanks again for explaining it so well. Usually me and you do not agree on healthcare issues, but this is one area where we seem to be on the same page.

As for diagnosing rare or very rare diseases, yes, it is possible, as you said. However, if you search for the rare disease I have in PUBMED, there are only 111 journal articles that have been written about it, and some are in foreign languages. The information on it is very sparse. I also doubt that it would be diagnosed by AI, as it effectively looks like "diabetes complications" (I have type 1 diabetes) and even though I had autonomic neuropathy at age 5, the onset of symptoms was very insidious.

> [...] to the point where it could be used to train [...] require a tremendous amount of human labor by expert clinician.

This is how it has been done for decades at this point (at least in some systems), and yes it is expensive. To really tackle things like above rare disease interactions, it would require at least an order of magnitude change, this is at least plausible; but would require some systemic changes.

Correct and thank you. Usually me and you don't agree on healthcare matters, but on this, at least we do. Your response is on point, and is exactly the issue.