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Comment by luma | Hacker News Reader

Brother-in-law graduated med school in the early 90s and has been a practicing ER physician since. We discussed this recently and he related that his advisors told him not to go into radiology back in the late 80s because the assumption was that computers were going to take over the field. He's not too far away from retirement and it's only now that we're starting to see some signs of this prediction from 30+ years ago.

As others in the thread note, there are plenty of concerns around operational use of AI solutions in the medical space, but radiology has a much larger target painted on it than other practices as a fair portion of the job (but certainly not all!) can boil down to high-skill pattern recognition from visual inputs. The current list of AI-enabled devices going through FDA approval is public, more than 3/4 of the list are targeting radiology use cases: https://www.fda.gov/medical-devices/software-medical-device-...

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The issue with radiologists is that on average they are able to spot ~35% of correct diagnoses, while the world's best radiologists ~45%. AI might get us to ~50% which is ~15% better than an average radiologist (who still needs to review it).

Where are you getting these numbers? Even a cursory search doesn’t put the numbers anywhere near such poor performance by real people.

AI at 50% would be notably worse (also where are you getting that number?)

From radiologist AI training datasets, evaluated long-term/post-mortem.

I hate to be “source?” about it but your numbers are so far off what every search result is showing.

I am not saying those are for all diagnoses, but for some tricky yet important ones (i.e. detecting them early might save your life).

You did not give specificity of any kind until now, and now I’m even more curious where these numbers are coming from.

Some data (average radiologist score):

Early-Stage Lung Cancer (via Chest X-ray) 33.3%

Clinical Staging of Stage I Pancreatic Cancer (via CT, MRI, EUS) 21.6%

Breast Cancer (via Mammography in Dense Tissue) 30%

Cuneiform fractures (foot, X-Ray) 0%

Midfoot fractures (general, X-Ray) 12.5%

Cuboid fractures (X-Ray) 14.29%

Navicular fractures (X-Ray) 22.22%

Talus fractures (X-Ray) 21.43%

Individual radiologists often scored 5% in those as well. The skill distribution is brutal.

If your original argument was “it could be useful for more difficult/niche observations” then I think most of us wouldn’t have objected.

I also really don’t understand why you still aren’t sharing any links. Is this all LLM-generated without citations or something? Where are you getting your numbers?

Sauce or gtfo

And you are going to provide the references that will sustain this opinion, so we can elevate it to a fact...

Its fine to ask for sources. It's also fine to not give sources when relaying information in freeform comments. It's not fine to ask for sources in the tone you are using though, as though you are annoyed and simply expect sources to always be included with claims. There are better ways of accomplishing your goals.

Someone drops very specific percentages about diagnostic accuracy....numbers that, if true, have serious implications for patient outcomes, and your concern is that I did not ask nicely enough for a source? I could not think of a more HN typical response...

I did not even call the claim false, even if it almost deserve it...I said, essentially ...let's see the references so we can treat this as fact rather than opinion.

What you did is write a longer and more prescriptive comment about my tone than anything anyone has written about the actual substance :-)). You tone policed a one line request for evidence while giving a complete pass to unsourced medical statistics presented as fact.

If we are ranking things that erode discourse quality, I would say you are higher on the list.

If you give specific numbers then I expect sources. If you give out incredibly bold claims then I also expect sources.

It's one thing to talk casually, in which case I agree with you. But as soon as hard numbers are on the table, it's no longer casual, and if you do not provide sources then the assumption has to be that you pulled the numbers out of your ass and you are not to be trusted.

To get around that, just don't provide numbers and don't speak authoritatively. It's very easy, I don't know why people speak authoritatively if they know they can't back it up.

The earth is 21,000 miles in circumference

"SOURCE?"

There's a middle ground here that is a grey area that you seem to be pretending is obviously navigated. You're speaking pretty authoritatively on this by the way. Do you have the moral, propositional logic, and epistemological justification for these claims?

I didn't make any claims, all of that is my opinion. There's literally no claims there. I just said that people who spew out numbers then can't provide a source aren't trustworthy - that's an opinion.

And there's obviously a difference between an established and obvious fact and a BOLD claim. This person made a BOLD claim. And provided numbers. To me, that requires a source.

Yes, there is a middle ground, but this isn't in the middle ground. I think this type of claim requires a source. A different claim, without specific percentages, would not. Or an obvious claim, like the Earth's circumference, also would not.

I’m not sure I find this to be a comparable example.

If someone was making an important calculation or decision based on the circumference of the earth, then they would likely want the number cited/confirmed and not just thrown out by a random person that doesn’t pass the smell test. “Radiologists are only right 35% of the time” does not pass the smell test and a cursory search makes the case even worse.

I assume the numbers are made up as an example.

I worry that rational takes like this end up completely lost in the battle between motivated parties who yell far louder, but have minimal investment in actual outcomes for those who will be depending on these technologies. The debate over self-driving vehicles is another example.

^ Knowing this, I would believe the best course of action for a hospital administrator would be to implement a "blind workflow" to reduce risk & lawsuits.

A radiologist should separately review a scan, an AI separately review it, and then combine the 2 results for review.

I have seen very conflicting data on this. You shouldn’t state it so confidently.

Maybe radiologist mean something different in my country, but here radiologist don't diagnose (i mean, except you see them for a broken bone or something), oncologist do. I did an observation internship with a radiologist when i was 20 (95% of my family are doctor/nurses/PT, i wanted to know what a degree in physics could help me do in the field, and radiologist was the only path to medecine from my initial formation where i only lost a year, and not two). You spend your time calculating doses, finding patient history, and calibrating machines, it's much more a technician role than a MD. In any case, and even if in the US radiologist diagnose cancer, that's such a small part of their job it shouldn't matter.

Persuade someone to run a prospective trial and show the outcomes. Everything else is bullshit

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