> They performed shockwave therapy on my shoulder even though a recent clinical practice guideline says clinicians should not use or recommend shockwave therapy for rotator-cuff tendinopathy without calcification; I was told during ultrasound that there was no calcification.

Ultrasound isn't a great way to assess for calcification. It'll find large calcification but easily miss small ones. Plain radiograph would be more helpful, but the MRI may have revealed it as well. Either way, shockwave therapy isn't harmful in the absence of calcification--it's just not helpful.

Edit: when a radiology report says something isn't present, there's always an implicit caveat that the finding isn't present within the context of the modality and images obtained. So an ultrasound report can state there are no calcifications while a plain radiograph can report the presence of calcifications without being inconsistent. Obviously very confusing to patients and people unfamiliar with medical jargon, but clarifying this in reports would make them sound even more qualified, "hedgey", and annoying to read than they already are.

This really is key. We know we can't trust the AI, but at the same time we're also more comfortable asking the AI for clarifications or confronting it. Not having a time-bound appointment or paying by the hour helps a lot. But even then, more information doesn't necessarily help!

I once brought my 11-year-old car, a Civic with 150k miles, to multiple garages. I figured I'd play the "second opinion" game to correlate what the garages recommended to decide on what needed to be done...

I got 3 completely unrelated recommendations, including one that I knew was invalid. I felt worse off than when I started!

The solution to uncertain information isn't more information, which the AI can certainly provide, it's better information, and AI cannot currently provide that.

I also had a pretty painful shoulder issue at one point, where the pain just wasn't subsiding for months. I tried massages and acupuncture as I didn't want to do surgery, but it wasn't helping at all. The thing that fixed it for me was just really focusing on doing pull-ups. I couldn't do them at all when I started, so I began with dead hangs and scapular pull-ups, eventually progressing to regular pull-ups, and then training with a "grease-the-groove" method once I could get a few per set. I stopped the training schedule once I was getting in around 17 pull-ups per set, and now just do 6 sets of about 7-8 pullups 3x per week spaced throughout the day. I'll also do some shoulder mobility drills [1].

Whenever I get lazy about keeping up with them inevitably discomfort will start arising again, but it goes away once I get back to strengthening.

[1] https://www.youtube.com/watch?v=vP8YmmRMz6I

Dr. GPT is a good brainstorming tool. It helps synthesize information in a way that primary texts don’t. But it does force you to say “that doesn’t make sense”.

I do think that people saying “doctors don’t know the state of the art” have a weaker case. If you think about it in terms of token density during pretraining and how post training datasets are constructed, I think it would take us a very long time to adapt to any fundamental shifts. If we have forgotten how to cure scurvy, how many journal articles would it take before we adapt to a discovery?

I wouldn't consider Claude itself to be the tool that does a job like this, but the tool that pulls in the best data and gives a supported suggestion. And then go through a number of iterations on where it failed to hone in its assessment.

Again, this is just one single person's experience. So not worth much.

ChatGPT surfaced a NIH study that concluded that 20% of people have allergic reactions that are isolated to a body location, and that shoulder "skin prick" testing may not reveal. I asked him about that and he said "that's not how allergies work". Full stop. He was unwilling to even look at the study.

He prescribed a CPAP and regular nebulizer treatments. Side story: the CPAP place sent me a SMS message that I couldn't recognize was not a phishing attempt, and when I reached out to inquire who they were they never replied.

So I decided: Let me just try taking a second-gen allergy tablet every day and see what happens.

My sinus infections have gone away. Previously I was getting a major sinus infection at least quarterly. Maybe he's right that allergies don't work that way, but allergy tablets have absolutely solved my problem. Which I'm thankful for because I tried a CPAP for a solid month a few years ago and I just could not get used to it, and was sleeping like crap.

One doctor diagnosis + LLM is gonna throw you off. You need more datapoints.

The LLM doesn’t need to be leading or whatever but then you can have a conversation with the patient. If their ChatGPT reports has differences it can be analyzed as well.

It feels like the time constraint of the 15m doctor sessions is the thing. But if prepared immediately after the scan then why not?

There is always time needed to factor in new developments and innovations and that’s fine. Just moving blindly work from human to LLM is wrong. But learning on and testing with all the ai tools incoming constantly won’t be a waste. There will be more and more tools in those processes outside of human judgement, better improve the workflows now to be able to test and plugin new models and systems when they are ready.

> As detailed in a new, yet-to-be-peer-reviewed paper, a team of researchers at Stanford University found that frontier AI models readily generated “detailed image descriptions and elaborate reasoning traces, including pathology-biased clinical findings, for images never provided.”

> In other words, the AI models happily came up with answers to questions about a supposedly accompanying image — even if the researchers never even showed it an image.

> As opposed to hallucinations, which involve AI models arbitrarily filling in the gaps within a logical framework, the team coined a new term for the phenomenon: “mirage reasoning.”

> The effect “involves constructing a false epistemic frame, i.e., describing a multi-modal input never provided by the user and basing the rest of the conversation on that, therefore changing the context of the task at hand,” the researchers wrote in their paper.

> The damning findings suggest AI models cheat by diving into the data they were given — and coming up with the rest based on probability, even if it’s almost entirely conjecture.

And well, yes, I have the appropriate life science degrees to navigate clinical trial reports and research publications, and that was likely indispensable for steering Claude Code where it went, the radiologist's caution is merited here. But it's just not amateur hour for me to do this, it's 2 decades of academic research in my rearview mirror.

https://www.nature.com/articles/d41586-026-01947-1

I've started asking my doctors whether they use AI, and if they say yes look for another one.

An AI telling you it could be X or Y because theory ABC… is the academic answer and a luxury clinicians don’t have. AI doesn’t give you what you want. I don’t see any added value in using generic AI models for this

I found that while Claude, GPT etc could describe an image, there was no way to link the description back to specific pixels in the image itself. Not even to a bounding box or segment.

If the author would actually go for a second opinion (maybe bring along the AI to let it explain it's findings), then the article could read as "AI did MRI analysis and proved my doctor wrong" (or: "AI did MRI analysis and failed").

It's not true that "AI makes mistakes" or "ChatGPT is sycophantic". It's just that sometimes the simulated extensions to the training material are accurate, and sometimes they're not.

IME, on an almost daily basis, claude.ai and Claude Code are confidently wrong about something, and use polished language to assert nonsense.[*]

If it's doing that on something easy, like factual knowledge available in text on the Internet, or programming code that can be inspected easily and follows well-known rules, and I can tell, because I understand those things... then there's no way I'm going to assume that Claude doesn't also BS when it comes to someone else's field. Especially not a field that requires some of the smartest people to go a decade of training, just to get started in the field.

[*] And if I confront Claude with its mistakes, eventually it apologizes, and acts as if it's learned something, again mimicking word patterns it's heard real people use and mean, without meaning any of it. I wonder whether the AI user experience would be better, if LLM-ish interfaces weren't implicitly created in the image of fake-it-till-you-make-it overconfident performative sociopathic techbros.

But are you all forgetting that they literally injected a homeopathic drug on the author?

Between that and Claude sometimes hallucinating, it’s probably worth encouraging patients to take second opinion always.