https://www.liveinsurancenews.com/health-insurance-claims-de...
Most physicians I know use ChatGPT. Although of course it's usage guided by an expert, not by the patient, nor fully autonomous.
Edit: People seem confused here. The study was feeding the AI structured clinical scenarios and seeing it's results. The study was not a live analyses of AI being used in the field to treat patients.
These "experts", they have no problem to tout anecdotes when it serves them..
> Three physicians independently assigned gold-standard triage levels based on cited clinical guidelines and clinical expertise, with high inter-rater agreement
And in most cases the diagnosis is the easy part. I mean we see occasional horror stories about misdiagnosis but those are rare. The harder and more important part is coming up with an effective treatment plan which the patient will actually follow, and then monitoring progress while making adjustments as needed. So a focus on the diagnosis portion of clinical decision support seems fundamentally misguided.
Yea, like how rich the patient is or if they are on insurance etc. I wish I was kidding.
I suspect many, many doctors also fail to regularly recognize medical emergencies.
Now, I don't agree that this is a good decision, but the point is, human doctors also often miss major problems.
We live during the healthiest period in human history due to the fact that doctors are highly reliable and well-trained. You simply would not be able to replace a real doctor with an LLM and get desirable results.
It's like people want to remove the physician or current care from the discussion. It's weird because care is already too expensive and too error prone for the cost.
I think it's rather people trying to keep grounded and suggest that it's not just the hallucination machine that's bad, but also that many doctors in real life also suck - in part because of the domain being complex, but also due to a plethora of human reasons, such as not listening to your patients properly or disregarding their experiences and being dismissive (seems to happen to women more for some reason), or sometimes just being overworked.
> You simply would not be able to replace a real doctor with an LLM and get desirable results.
I don't think people should be replaced with LLMs, but we should benchmark the relative performance of various approaches:
A) the performance of doctors alone, no LLMs
B) the performance of LLMs alone, no human in the loop
C) the performance of doctors, using LLMs
Ideally you'd assess the weaknesses and utility of both at a meaningfully large scale, in search of blind spots and systemic issues, the problem being that benchmarking that in a vacuum without involving real cases might prove to be difficult and doing that on real cases would be unethical and a non-starter. And you'd also get issues with finding the truly shitty doctors to include in the sample set, sometimes even ones with good intentions but really overworked (other times because their results would suggest they shouldn't be practicing healthcare), otherwise you're skewing towards only the competent ones which is a misrepresentation of reality.
Reminds me of an article that got linked on HN a while back: https://restofworld.org/2025/ai-chatbot-china-sick/
The fact that someone would say stuff like "Doctors are more like machines." implies failure before we even get to basic medical competency. People willingly misdirect themselves and risk getting horrible advice because humans will not give better advice and the sycophantic machine is just nicer.
If you look at online reviews, doctors are mostly rated based on being "nice" but that has little bearing on patient outcomes.
A few weeks before the ER, I was having stomach pain. I went to the doctor with theories from ChatGPT in hand, they checked me for those things and then didn't check me for what ended up being a pretty obvious issue. What's interesting is that I mentioned to the doctor that I used ChatGPT and that the doctor even seemed to value that opinion and did not consider other options (and what it ultimately ended up being was rare but really obvious in retrospect, I think most doctors would have checked for it). I do feel I actually biased the first doctors opinion with my "research."
Why can't you name them, and give us some context? Is this based on public info, or not?
I'm not so sure. Doctors are trained to check for the most common things that explain the symptoms. "When you hear hoofbeats, think horses not zebras" is a saying that is often heard in medicine.
ChatGPT was trained on the same medical textbooks and research papers that doctors are.
Yeah hm I wonder what the difference could possibly be.
It may feel easy to say doctors should just consider all the options. But telling them an option is worse than just biasing their thinking; they are going to interpret that as information about your symptoms.
If you feel pain in your abdomen but are only talking about your appendix, they are rightfully going to think the pain is in the region of your appendix. They are not going to treat you like you have kidney pain. How could they? If they have to treat all of your descriptions as all the things that you could be relating them to, then that information is practically useless.
I have a family member who had a "rare but obvious" one but it took 5 doctors to get to the diagnosis. What we really need to see are attempts to blind studies and real statistical rigor. It's funny to paint a tunnel on a canvas and get a Tesla to drive into it, but there's a reason studies (and the more blind the better) are the standard.
This has been a big problem in medicine since the early days of WebMD: Each appointment has a limited time due to the limited supply of doctors and high demand for appointments.
When someone arrives with their own research, the doctor has to make a choice: Do they work with what the patient brought and try to confirm or rule it out, or do they try to walk back their research and start from the beginning?
When doctors appear to disregard the research patients arrive with many patients get very angry. It leads to negative reviews or even formal complaints being filed (usually from encouragement from some Facebook group or TikTok community they were in). There might even be bigger problems if the patient turns out to be correct and the doctor did not embrace the research, which can prompt lawsuits.
So many doctors will err on the side of focusing on patient-provided theories first. Given the finite time available to see each patient (with waiting lists already extending months out in some places) this can crowd out time for getting a big picture discussion through the doctor's own diagnostic process.
When I visit a doctor I try to ground myself to starting with symptoms first and try to avoid biasing toward my thoughts about what it might be. Only if the conversation is going nowhere do I bring out my research, and then only as questions rather than suggestions. This seems to be more helpful than what I did when I was younger, which is research everything for hours and then show up with an idea that I wanted them to confirm or disprove.
A doctor is typically scheduled at 6 patients/hour. In that time they also have to chart, walk between rooms, make up time for the other patients that inevitably went over time, et cetera. The doctor you're seeing probably has a goal of only talking to you for 3 minutes.
Still regularly get wrong information from google’s search AI.
Really starting to wonder if common sense is ever going to come back with new tech, but I fear it is going to require something truly catastrophic to happen.
The fact that the model most hyper-optimized for cheap+fast makes mistakes is not a particular compelling argument.
[1] https://openai.com/index/introducing-chatgpt-health/
[2] https://cdn.openai.com/pdf/bd7a39d5-9e9f-47b3-903c-8b847ca65...
Win win right?
A friend of mine had an accident. He was taken to the emergency room, but the doctors there thought his injuries were minor. My friend insisted that he was bleeding out internally. They finally checked for that, and it turns out he was minutes from dying.
AI wasn't involved in this case, but it's good to have both AI and a trained doctor in the decision loop.
ml_giant•1h ago