I've seen a lot of friends and family members almost immediately get offered surgery for shoulder pain. It's just often the default for people that do surgeries for a living.
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.
I don’t understand the negative reactions. Medical care as it exists requires the doctor and patient to have their brains switched on. I’ve almost never had a problem where a doctor provides me with a diagnosis and I go about my day. Most of the times that I have, I’ve been confident about the problem and known what I needed. The doctor was a barrier to accessing care.
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 asked a bird about my father's potential prostate cancer. It gave extremely good advice.
Personally my favourite feature of the new ai world is not when I use it directly but it's when one of my managers uses it to try to fix a problem, then issue to me their findings and I have to defend my process to someone who understands neither my process, their suggested solution nor often the problem they're solving in the first place.
~2 years ago I used ChatGPT "deep research" to investigate a chronic sinus infection I'd been fighting for ~3 years. After seeing 3 GPs and 3 visits with an ENT, I fed all the observations I had into the AI. In particular, I couldn't get the ENT to explain why he visually saw, via a scope, evidence of allergic reaction in my sinuses, but then later concluded, after an allergy test, that it couldn't be treated via allergy medication. I asked this question a few times and he just never answered.
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.
I would not trust AI on images. But I once had ChatGPT tell me that an MRI report was very likely to be incorrect based on the text, and offered a different diagnosis. Since it was semi insisting, I visited another doctor who made me do a retest. Long story short, ChatGPT was correct.
Again, this is just one single person's experience. So not worth much.
You should always be getting a second or third opinion from real doctors for matters like surgeries, radiology, etc.
One doctor diagnosis + LLM is gonna throw you off. You need more datapoints.
That might be doctors new nightmare: people who second guess everything with AI. Previously it was "google your symptoms".
I would like if we could have a site where you submit your MRI then doctor commenters anonymously post their opinion. In general I want a forum where.. when people come with questions for which there are varying opinions we don't just have people leave their 2c and then jet. The thread persists, duplicated ideas get merged, erroneous statements get purged and gradually we refine shining truth
I did the same exercise here with medical reports and CT scans for a friend's cancer diagnosis and I got ahead of the oncologists predicting they were about to be cured. Spoilers: yep, cancer free now.
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.
Why wouldn’t you as a doctor by standard run the images through a certified compliant LLM? The actual cost won’t be it and then you can see if you get any new ideas from it. See if it’s just wrong or that it spotted a little detail you missed?
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.
> My hope is that in a couple of model generations, we'll trust AI to review MRIs the way we trust it to proofread our emails.
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.
Always worth a share for this scenario. It's not clear if LLMs are capable of doing actual analysis on medical imaging. For details see this article https://futurism.com/artificial-intelligence/frontier-models...
> 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.
Can any LLM give you the rough pixel coordinates of an item it identifies in an image?
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.
The thing that annoys me about AI discourse is that AI is a mathematical technique of rapidly increasing efficacy, and yet everyone personifies it. It would help if every time someone said "AI" they supplemented "a mathematical method where extensions onto a very large corpus of information are statistically simulated".
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.
Hey, glad you did that , I have done the exact same think last week but the radiologist interpretation and claudes interpretation was pretty much the same ! you want my doctors number ? lol
I would not use Claude to get a second opinion on anything that’s an image.
Radiologists very often have to weigh up different theories, guidelines based on the symptoms. The certainty of their diagnosis is their added value, or if they don’t know they will tell you why.
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
Hey OP my wife had a subscap tear and went through with surgery. Recovery was ROUGH, she couldn’t use that arm at all for almost two months. It’s amazing how much this can cripple a person, we don’t realize how much we use both our hands for our daily lives until one is gone. Even basic stuff like cooking, bathing, etc. If you can avoid surgery you should. Try doing the Buckburger 12 (spelling?) shoulder physiotherapy regiment. You’ll need to even if you get surgery, but this can help with tedonopathy. Also try to identify what is causing the repetitive stress and cut back on that activity.
Getting an actual second opinion seems like the next step?
I have used Gemini 3.1 Pro through CLI to analyze my DICOM images. It gave me the same diagnosis as radiologists. But it was just interesting test
Right now the article reads as "AI can play doctor if you give MRI scans".
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").
I wouldn't trust anything from Claude here image-wise (maybe to get a 2nd opinion on the report itself and treatment it's reasonable), but also, on the cases there is something something serious, go to at least 2 different doctors and if they have different opinions go for a 3rd for a decisive vote, besides doing your own research (it's not that uncommon for hard cases to be badly diagnosed).
This could be a starting point for consulting a different human expert for a second opinion (e.g., specific questions to ask about), but I wouldn't put much trust in Claude alone on this.
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.
Everyone talking about how doctors know better or have some context that is not shown here.
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.
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I'm a radiologist but can't really weigh in without seeing the full 3D MRI dataset. Regarding this point:
> 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.