I used Claude Code to get a second opinion on my MRI

> There's something incredibly peaceful about being in the hands of an expert you trust. [...] AI can absolutely shatter that feeling in an uncomfortable way [...] but I don't know if I can fully trust AI either.

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.

A few years ago (before the AI craze), I was misdiagnosed with tuberculosis. I had a chronic cough, and an outsourced radiologist at a clinic found signs of tuberculosis. The findings were sent to the city's tuberculosis hospital, as required by the country's law. The doctors there took the radiologist's conclusion at face value and required me to stay at their hospital for at least 8 months under a strict, prison-like regime. There was no option to say no, because I was considered some kind of biohazard, and by law I had to comply.

Before I was admitted, I quickly found another radiologist, who diagnosed pneumonia instead. I sent his report to the chief doctor at the tuberculosis hospital, and after some deliberation they concluded that the original reading was wrong. Turns out the doctors there can't read scans at all and just believe whatever a radiologist says...

The funny thing is, they had already officially put me on the tuberculosis register and didn't want to admit they had made a mistake. So instead, they simply gave me another paper saying that I had been cured of tuberculosis by them... in 7 days. I'm probably the only person in the country to defeat tuberculosis in a week :)

So if you don't trust the radiologist/doctor, maybe find another doctor if you can afford it? You can compare their conclusions and see if they match. Two unrelated doctors or radiologists saying the same thing is probably about as close to the truth as you're going to get. I'm not sure though whether I should trust AI or humans more. AI can hallucinate, but I've been misdiagnosed by humans so many times too...

Radiologist. I don’t read MR shoulder exams in my day to day practice, but from the few pictures shown , I can’t conclusively disagree with the original report.

These models are generally terrible at reading medical images. The amount of public training data on the internet compared to the number of scans a radiologist reads in training is minuscule. There’s obviously a ton of medical images in general but very few, and even fewer along with a report are available on the internet publicly for download.

There are vision language models coming out of research labs that are excellent in describing and localizing findings. Still at the level of a 1st or 2nd year radiology resident, but as we all say - this is the worst the models will ever be.

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.

It funny to see the community here expects the human body to be treated like a deterministic function: for input X expect output Y - and that transfers to diagnosis - people expect to receive the same diagnosis from different specialists for the same issue.

Given human body complexity, the diagnosis is a compound output of the experience, knowledge gained throughout the career and diagnosis methods/equipment, the title (like Dr) is a certification imposed by the state so its "safe" to let people practice since they passed "the bar" - but that doesn't imply everyone will be treating the same.

Some specialists update their knowledge monthly, some yearly and some don't do it at all, there are so many variables in play here (geo, politics, even weather haha).

Having said that, choosing the specialist is really important, getting opinions about their practice and their speciality, you can only maximize your chance of getting the right diagnosis, but don't expect to get it right just because somebody is called a Dr.

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.

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

~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.

As a radiologist I have found Claude and ChatGPT to be absolutely terrible at MRI and I would not trust it one bit. It has its merits if you need to research stuff that is more text based, but radiological images is just something that they cannot interpret good enough (yet)

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.

That might be doctors new nightmare: people who second guess everything with AI. Previously it was "google your symptoms".

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?

"A 2026 Finnish study published in JAMA Internal Medicine that used magnetic resonance imaging (MRI) scans to look at patients’ shoulders found that 99% of Finnish adults over 40 have at least one rotator cuff abnormality." https://brainlenses.substack.com/p/abnormality

Incidental Rotator Cuff Abnormalities on Magnetic Resonance Imaging https://jamanetwork.com/journals/jamainternalmedicine/fullar...

I thought this was an interesting experiment and I repeated it with my own DICOM. Results are terrible. Claude has complete opposite diagnosis on my ACL, mensci and cartilage.

Claude: Primary finding: Complete ACL tear with the classic pivot-shift bone bruise signature (posterior lateral femoral condyle + anterior lateral tibial plateau edema) and large hemarthrosis. PCL, MCL, LCL, menisci, and cartilage all intact.

Radiologist: English translation of findings & conclusion: Mild joint effusion. No Baker's cyst. Post-ACL reconstruction with minor cyst formation in both the femoral and tibial bone tunnels. The ACL graft shows heterogeneous signal but no complete or recurrent rupture. PCL and collateral ligaments intact. The lateral meniscus appears abnormal, likely from prior partial meniscectomy, with significant cartilage loss (partly Grade 4) at the posterior lateral compartment, osteophyte formation, and reactive bone marrow edema. The medial meniscus shows diffuse signal change from prior repair but no recurrent tear (specifically no recurrent bucket-handle tear). Mild chondropathy with focal cartilage loss on the lateral side of the medial femoral condyle. Cyclops lesion present. No definite loose bodies.

Frustrating post. This gives rightful ammunition to the calls of "LLMs need to be avoided for anything medical". Even though the issue is that they're asking it to interpret images. They need to be avoided for that, but that doesn't say much about their medical accuracy outside of image interpretation.

It would already be a huge benefit to 90% of people worldwide if the very first part of most hospital visits would be outsourced to frontier-level LLMs. Yet this kind of misuse just gives the medical industry a stick to beat that idea into the ground.

Oh well, I'm sure there will be at least a few countries that will indeed embrace frontier models for initial diagnostic medical purposes. Maybe medical tourism destinations. But it's unfortunate for those who can't afford the trip.

I feel like I'm going nuts.

There are other commenters saying this is a good practice they've also done for other injuries. You are saying you are an actual radiologist and immediately clock the problems with its advice.

I have seen this pattern over and over again. Anytime someone is an actual expert at anything, AI output appears insufficient or incomplete or outright misleading. It is only when you do not know what the AI is being asked to do is it likely you will find the output helpful.

This is itself alarming to me, but no one else seems to find this to be quite damning for the AI services being offered, preferring instanced to be wowed by the convenience and speed at which they can be delivered unreviewed and unproven information.

> 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.

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.

How do LLMs get information from images? Do they have to run essentially the opposite of an image generation model, taking an image and converting it into a description? I'm just concerned that the description wouldn't be able to encapsulate the information needed to differentiate exactly what is wrong with a shoulder. The image -> text model would need to know what it should actually report back to the LLM about the image, so that it doesn't just say "this is an MRI of a shoulder" or similar. It would be like a layperson describing a bridge, and asking an engineer if the bridge is safe based on that description

As someone who has had shoulder issues for the last 25 years or so, including partial tendon tears, I can tell you that even if your tendon would have been damaged, the treatment would have been strange. With moderately damaged tendons, you want:

1. stop any inflammation, by taking NSAIDs for a few days

2. detect and correct any behavioral patterns that could have caused the presumed overwear of the tendon

2. start physiotherapy to strengthen those muscles that can take over the load from the damaged tendon

These are not quick fixes, because quick fixes don't exist here. Stuff like shockwave treatment, massages etc will only lessen the problems for a few hours at most, after which they will come back.

Was it 2016 when Geoff hinton said that radiology was a dead career?

Well, we now have the best model of our time (trillions of $$$ of investments) telling us something completely different(and wrong) from a human expert. I would really like someone calling out dario, sam, elon on these things and hear their explanations but alas, a man can only dream.

Yeah, one of the big problems with that is that Claude/ChatGPT doesn't perceive images the way humans do at all, so when you upload an image to them, it gets tokenized in some form. This is why most LLMs are really, really bad at spatial recognition for image editing purposes for example.

So, unless you can turn the image into a natively tokenized format like JSON or something that somehow accurately tokenizes what's on there, I would NOT trust Dr. Claude's analysis. If you want a second opinion, talk to another doctor. A human doctor.

> There's something incredibly peaceful about being in the hands of an expert you trust. You don't have to worry anymore and can let them guide you through the process.

> AI can absolutely shatter that feeling in an uncomfortable way ...

I see this as a field report in a time of fundamental transition, from a world without AI, to one that accommodates/incorporates AI. For this to happen, AI will need to become more trustworthy. As for the U.S. medical system, it can't get much worse.

I recently had a similar experience (meaning walking a fence between old and new methods), where I was told I could get an appointment with a human medical practitioner in nine months. So, to resolve my anxiety I consulted AI and got an instant diagnosis, one that was later confirmed by the inaccessible medics.

Being a born skeptic I wasn't going to act on AI's diagnosis, I just wanted to know what was going on, resolve some uncertainty. Another advantage: an AI chatbot doesn't say, "Wait, you're on Medicare? Hmm. See you in nine months."

Don't take this as an endorsement of AI's diagnostic abilities -- it's way too soon for that. In my case it was a slam dunk, about a condition I knew nothing about.

The only part of the message I think it would be interesting to the author: what if you set two instances to prove each other arguments wrong considering that each reads one of the report as their POV?

I didnt see the full process but I used unet models for tumor detection so I am somewhat familiar with the possible caveats of any evaluation from a engineer perspective.

First, I would like to point that unfortunately, it is not uncommon to go to two different human doctors and also get two unreliable diagnosis and treatment. The biggest problem, in the way people plan to use ai on health is the lack of liability.

A bug on a regular old web site doesn't kill anyway nor cause pain and suffering (most of the times) but misdiagnosis + the fact that a model is very good on presenting arguments even when it is completely wrong.

Claude code, and I am talking about opus 4.8 here, can tell rivers of information about code pattern and develop the poopiest code the next line.

This is a machine that will deliver a sort of templates document based on the input information but it is not exactly doing the work if you don't directly it to do it right constantly.

Because the model isn't thinking I wonder what happens if you set multiple agents to communicate and defend their point with some sort of harsh penalty prompt for not fulfilling its goal. There are some safety system prompts on Claude models that will trigger it to be very carefully to write. Like: you cannot make mistakes. "You need to ensure that it is correct or someone might end up hurt or even dead"

But you would need two agents and a setup to communicate via pipes or files.

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.

I recently had a pretty bad injury and out of curiosity I asked Gemini what it thought based on some CT scan slice images (and no other information). Surprisingly it came to exactly the same diagnosis and treatment plan as my doctors, but the big advantage is that I could ask it follow up questions any time, whereas the doctors barely explained anything.

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 would not use Claude to get a second opinion on anything that’s an image.

Personally I do this as well now with a lot of stuff. I've recently had a lot of issues with my knee, which was operated on about 20 years ago because of a torn cruciate ligament, and now it was acting up again. The specialized doctor did a x-ray (which I thought was pointless because I was sure it was not bones related). Long story short, my left knee is 20 years older then me because of increased knee wear and tear. I don't have a doubt the doctor is right, but I did doubt I memorized everything correctly, and later on I had some more low effort questions I didn't want to bother them with like what movements should I prevent and specifically what training I should be doing at the gym.

Thankfully I got a pretty detailed report that I couldn't read because of all the medical terms. I've fed this to Claude and asked for a human readable conclusion and it repeated pretty much everything the doctor told me, which was great, I now have a readable report for future reference. Secondly I asked it questions about what movements I should and shouldn't do, and it eventually I made a gym plan to improve stability and prevent any more wear and tear in my knee. Lastly I validated this with the assigned physiotherapist, and the plan I created with Claude was perfect!

I probably won't ever use AI as a second opinion, but I would definitely use it to ask numerous silly questions that would help me in day to day life.

Medical opinion will remain one of the last frontiers of LLMs. There so many critical factors that are inappropriate for them. They cannot perform a clinical exam, they have to collect the needed exams and most importantly a life might be at stake (OK, you cannot die from a shoulder problem but you can become handicapped forever).

All that said, as a doctor I am totally open and even happy when a patient refers they took advice from AI. I explain the holes of their reasoning and integrate it with mine. It helps rather than hurts the patient-doctor connection.

I don't know which country this is but this sure seems like a country where doctors have an incentive to maximize the amount/cost of treatment.

I've seen the two extremes in different countries; either they have a tendency to maximize the complexity of the medical situation, or they minimize it "Don't worry, it's just stress" - I've been to different doctors in different countries and I see a pattern based on the country and the incentive structure. In some countries, they will send you off to do a scan for the slightest malaise.

I don't think it's about quality/coverage of public healthcare (at least not on its own; I have not seen a clear pattern across this axis). I think the difference is to do with the referral system. In countries where you can't go directly to a specialist and need a referral from a General Practitioner/Physician first (I.e. in order to get a refund), you tend to get more false negatives from the GP which block you from going to the next stage "It's nothing, just stress-related." In countries were you have the option to go directly to a specialist, they tend to be much more trigger-happy in terms of giving you a full workup and GPs/Physicians will more easily refer you to a specialist.

And I feel like the attitude extends to the specialists themselves. I suppose making people go to a GP first creates a kind of efficiency and predictability which alleviates pressure to exaggerate the severity of the situation.

We provide a second opinion service with certified human radiologists, if anyone's interested: https://expert.med

My only issue with this was the restriction of "Do not look at any data outside of our working folder" is preventing the tool from doing what it does best. I would have given it access to PubMed to pull the latest research on the subject and validate.

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.

> It might seem obvious to coders, but the difference between Claude Code and Claude.ai's chat is enormous, even if those two run the same model.

In my experience, Claude Code is vastly better for doing tasks, writing code, etc., but Claude.ai is better for analysis and high-level planning. When I'm working on a new project, I've started using the latter to do the initial planning, get feedback and draw up a spec, which then goes to Claude Code.

For this project, I probably would've done something similar - use CC to get whatever you need out of the image files, but have Claude.ai do the actual review/diagnosing.

Either way, I often think about how far behind most of the world is in really understanding AI. The overwhelming majority of people would never guess that you get vastly different outcomes from the exact same model in a different harness (tbf most people don't know what a harness is). I spend hours every day using AI for a broad range of tasks and still feel like I know a fraction of what there is to know. I haven't even tried the new GLM model (or really any of the open source Chinese ones of the most recent generation). With so many people thinking that the free version of ChatGPT is SOTA AI, a lot of folks are in for a very rude awakening at some point soon.

I was diagnosed with a rare blood disease called Essential Thrombocythemia (ET) which is part of a group of diseases called myeloproliferative neoplasms. This happened about three years ago. Recently, I decided to get a second opinion and my new specialist changed my diagnosis from ET to Polycythemia Vera (PV). She also highly recommended I quickly go and give blood to lower my haematocrit levels as it put me at a much higher risk of a blood clot. This is standard practice for people with PV but not people with ET. I decided to put the details into google AI in the same way that the original specialist used to diagnose me. Google AI predicted I very likely had PV instead of ET. I also asked Google AI how one could misdiagnose my condition with ET instead of PV and google correctly explained how. My specialist had used my high platelet count and blood test that came back with a JAK2 mutation then after a bone marrow biopsy to incorrectly diagnose me with ET. My high hemoglobin levels should of been checked by my first specialist as an indication of PV not ET. Only the second specialist picked up on this. Google AI took five seconds, and is free. The specialists costs $$$ and took weeks.

I'm pro-AI, but when I can't even give Claude a photo of my fingers clearly on four different piano keys and get an accurate result of which keys I'm pressing, I'm bearish on its visual analyses. (With that said, I imagine it's been trained on more photos of MRI scans than people playing piano, so I could see how it might provide interesting ideas for a radiologist to consider.)

Seems like we've forgotten something already? LLMs are bad with the butterfly effect by their very nature. An extremely slight phrasing change can absolutely trigger a deterministic output decision that is out of touch with reality. Tuning only helps if there is training from a previous input. As far as I know (casual research), there still isn't a great solution to this, only marketing hype.

I had shoulder pain about ten years ago. Had an MRI. Found evidence of a tear. Was told I would need surgery and referred to a sports medicine doctor. He looked at my MRI and said the real problem was my shoulder was frozen, and he could do surgery but the PT after is what would actually be what helped me. Two radiologists and two doctors saw my MRI before this moment. Sure enough, with a little PT I got better.

I’ve had several more medical blunders since then, including a doctor telling me my problem is to lose weight 48 hours before going into emergency surgery.

What I have learned is to be weary of any time I feel like I’m in a “funnel.” Once you’re in the funnel, no one is thinking critically about your issue any more. One person said they found X. Next person reads that and assumes Y and recommends Z. And so on until the alpha is multiplied to hell. Lots of treatments that don’t hurt but don’t help and run up insurance.

I have since used AI the last couple years and it has either concurred with my doctors or given me enough ammo to challenge them. If I were the author, I would trust neither but use Claude to ask how to go back to that clinic and challenge the diagnosis.

Getting an actual second opinion seems like the next step?

> 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.

the doctors may have financial motives to suggest unnecessary treatments. but i fear, by the time we'll have models powerful enough we'd be _theoretically_ able to trust their expertise, the financial motives will have shifted to the model creators.

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

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.

Went to a new dentist recently and his staff took x-rays of my teeth. I was then waiting for him to come speak with me about what the x-rays show him yet i just took a pic and uploaded it to Gemini. 9 months back my previous dentist said i should have a filling or potentially a crown was needed. I told Gemini this and that ive only about 3 fleeting pain issues in that area. With the x-ray and that info Gemini told me the exact same thing the dentist later came in and told me. If pain comes back and for long periods of time then there's an issue as the x-rays look fine.

Overall i see a great opportunity for x-ray techs (radiographers even when Jensen from NVidia says the first field he recommends not getting into - Radiology which is the step above) to open their own businesses for people who want to use AI for self care and help. Have one doctor or dentist on staff to use as needed.

Go with your report back to your doctor.

A family member has cancer and we treat chatgpt as part of the team (our doctor's words). I ingest everything into it, work with it to make a good report. Then at the next visit we review it.

This gives you the best of both worlds. You get peace of mind and the doctor explains why and how the agent was right or wrong.

Twice now we've caught consequential mistakes (wrong pain medication and incorrect notation of the exact mutation that he has). Which have made a difference to his quality of life and treatment path.

Most of what the doctors have said is in line with the agent but when there have been disagreements they've been very reasonable. Sometimes the doctors have gone with the agent's version sometimes they've explained why that's inappropriate.

If you see an orthopedic surgeon (the much more common name for this type of doctor in the US) about almost anything you will almost certainly end up with an MRI (good chance your insurance won't cover this fully) and some kind of recommended intervention.

Although it does not handle MRI files yet. I opensourced an AI workflow that helps in figuring out issues with my family.

https://karankurani.github.io/OpenCareLoop/

It has helped me personally solve longer chronic problems in my family that doctors just dont have the time to go into indepth due to their (understandable) lack of time.

Its in alpha and AI hallucinates. Use with care. Feedback welcome.

An AI agent for personalized healthcare is inevitable. The cases such as the one posted are all solvable with time. AI has hallucinated and continues to hallucinate but the value we get in the space of coding can be extended to other domains.

A coworker just spend a weekend with AI analysing his image data. No problem detected. The official diagnosis came later: he had a serious degenerative problem.

These models don't have curated image exams in their training data. Your can't trust them.

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.

> So I'm left in a state of limbo where I either try my luck with another doctor or wait and see if my shoulder gets better with the rehab I'm doing.

Get a second opinion from another doctor. If that’s inconclusive, see three.

As a neurologist I read often imaging findings myself. However, one ability of the radiologists I appreciate is their ability to discern through artifacts by years of experience. I am not convinced the current AI crop can reach this level of discerning yet. But I am pretty sure they will reach us and surpass us there as well.

For the moment, I would prefer the final opinion always to be from a human (the human-in-the-loop approach in medicine). Best course of action is to run these LLM assessments and bring them to the next appointment and challenge constructively the doctor.

> There's something incredibly peaceful about being in the hands of an expert you trust. You don't have to worry anymore and can let them guide you through the process.

> AI can absolutely shatter that feeling in an uncomfortable way...

As a mental experiment, think how things would look like if the AIs were right more often than doctors. Then living longer and being healthier would imply living with a lot of "technical medical worries" that you don't longer get to outsource to a black-boxy human wearing whites. I know some people who are already ridding that train.

As everyone knows here a large language model using probabilistic next phrase approach will not be able to "diagnose" results from an MRI - at least not with enough confidence. It lacks the patient's history and a snapshot along with very varying datapoints in the training set will lead to "approximate" results. Not what a true doctor with a 360 view of a particular patient's health would be able to diagnose. That 'approximation' will get "better" in time - which only means the results will be replaced by yet another approximation.

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.

I tried the same on images of disks in my back. The ai picked a slice not from the middle and used that to say they were too small (since it was looking at a slice towards the edge) and basically told me my life was over and my pain would last forever.

Luckily my disks were fine. Wouldn't trust it. Additionally, an MRI of a pain-free, healthy human still would show lots of things and damage. Unless it coincides with a symptom, it's probably harmless. That's why the history is important when looking at images. Can't just upload something and hope for findings.

> They injected me with Traumeel, which is registered in Germany as a homeopathic medicine "without a therapeutic indication".

This single sentence provides a huge clue about what’s going on: This person’s medical team is not good. It’s not hard to get an LLM to perform better than a team that is injecting homeopathic botanical formulations and performing procedures that aren’t indicated for the condition.

I think the real takeaway from this article shouldn’t be “ChatGPT is better than doctors”. It’s a story about LLMs identifying that someone was not in good hands.

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.

the more I think about what intelligence really is and what it is about humans that AIs seem unable to replicate, the closer I come to the conclusion that personality is a huge component of intelligence. Certain problem spaces have a structure such that personality differences are stripped away, like in math problems for example, but more and more I am genuinely starting to believe that personality drives intelligence.

There is an undeniable mechanical / logical / objective component to intelligence that acts as the machine to get answers, but I am becoming ever increasingly convinced that you cannot actually separate this machine from personality and still perform at the highest level it is capable of. Communication has its own intelligence limits, and I do not think the marketing angle of "putting intelligence on a meter for you to buy" is going to be an actual real application of intelligence. Not without also outsourcing your personality or being satisfied with a flanderized impersonator of yourself as part of the intelligence

it may seem like this sort of thing should be ignorable for analyzing an MRI, that it's an objective conclusion. But medicine is not really as black and white as it seems. Doctors often have different opinions and they are credible. scans are not oracles, interpretation is involved, as well as a measurement of faith in what the patients body is able to do on its own and what it cant. hard to describe in a simple comment, but the point is that medical diagnosis are not exaclty something that can be packaged into perfect products for consumption to turn into the 1 and only treatment that's best for you

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

Recently I was at the doctor for a very minor sports injury ("tennis leg"). The doctor — who was in his 50s — was explaining the degrees of the injury to me, and quoted ChatGPT as the source, along the lines of "ChatGPT usually says you have to rest for.." I thought it's quite funny, but after thinking about it, it's really no surprise that doctors also use AIs to look things up / clean up their diagnosis.

> There's something incredibly peaceful about being in the hands of an expert you trust. You don't have to worry anymore and can let them guide you through the process. AI can absolutely shatter that feeling in an uncomfortable way

It's always something along the lines of incredibly peaceful, insanely powerful, extremely interesting, also scary and uncomfortable meanwhile feel like magical super powers and science fiction.

I'm telling you... words have lost meaning.

This seems less a demonstration of competence than of accessibility.

Often we only get 10-15 minutes with the one health professional that makes a determination and sets the path of your life for some time.

As opposed to being able to spend hours with an LLM that in many ways feels more sympathetic and helpful - even though it's competence is in question.

So here we are:

1. with doctors processing patients every 10 minutes like a machine.

2. and machine's processing, for a patient, at any hour like a human.

Imaging is one area where patients will be able to become more educated to ask better questions.

The areas of premature heavy interventions can be a challenge, especially where there might be room for interpretation and the medical professional didn’t share all possible options.

It’s critical to ask all professionals for all possible options and write each down as they write and explain it. No one’s perfect, and not everyone is negligent or malicious.

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).

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 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

I put a MRI of my body part into Gemini 2.5 Pro (for fun) and it said it was my brain. These models don't necessarily have that data.

Thank you for sharing. I'm about to get my MRI scan on my right shoulder tomorrow. Now I'm wondering what I'm going to do even if the result shows benign. Certainly, I would double check the result if it's concerning, should I also check a comforting result in case the truth is less comforting?

I was building a pc and the ai was hellbent on saying either the cpu pins are bent or motherboard is faulty. Both giving me a panic attack. The solution came from updating bios which i had done so ai ruled it out. But the shop owner did the bios update again and it worked

I had similar experience, Claude made report of MRI for achilles tear, it measured the gap, but it was completely hallucinated. Achilles tendon is black on the MRI, it instead measured 13mm distance between two completely different things (looked white), the radiologist looked at and saw no gap at all

I use LLMs every day and value the benefits they offer, but this approach seems misguided. A smarter way to use them would be to consult the LLM before seeing the specialist and ask it to bring you up to speed on capabilities/limitations and develop a list of important questions to ask.

If you ever get a MRI!

I'd like to have one for my broken shoulder, but they decided the x-ray is good enough before my shoulder OP. At least I got a date for my shoulder OP one year after the accident. Everything's perfect in Germany.

Given the tenor of the comments on this article, I think reading TFA is super important, especially the author's disclaimer at the end, where they state that they're definitely not blindly trusting the AI at this stage, just that they find the differential unsettling.

I am reminded of the old saying that anyone who diagnoses themselves has a fool for a doctor,

I'm surprised about the 266 MB of DICOM images, I've never had an MRI but my CT results are generally between 1-2GB (zipped) and I always assumed an MRI would have more data, guess I was wrong about that!

As a developer I have many times seen Claude's models confidently hallucinate, jump into conclusion. Fable though I used just for 2 days, didn't experience it much in the short-term.

German doctors are very prone to quackery. Including their nurses.

I've overheard a nurse at a university hospital argue with patient who used tape on himself about the color of the tape. She was worried he might use the "wrong color". Again: at a university hospital, where they teach MDs. Half of them recommend homeopathic remedies

In short: quaks.

AI use is such a polarizing topic anymore. What ever happened to just waiting and seeing how it all plays out? Since probably none of us is going to be able to predict it anyway.

I would trust a doctor with decades of experience and his diagnosis and treatment plan than some LLM.

It like using WebMD for any ache and pain and it is saying it might either be Lupus or cancer.

Anecdote on healthcare, adjacent to this.

My dog had been acting off. Wouldn’t eat, was hunched over, looked sad. We took him to a local vet who did an X-ray because they suspected a blockage. They didn’t see one, so they sent us home with standard pain meds.

Randomly, we had a dinner party that night and another vet was there. She heard the story and immediately said, “Go home right now and take your dog to an emergency vet with ultrasound.”

Turns out, at the time, most vets had been trained to use X-rays to look for blockages, but newer evidence showed X-rays were only something like 20% effective compared to ultrasound, which was closer to 95%. (forget percentages but somethign like that)

The ultrasound found an avocado pit stuck in his intestine. He had emergency surgery that night.

That chocolate chunk of an English Lab ended up living until 15, and only needed two more blockage surgeries after that...

I know doctors hate patients reading the internet, and LLMs are going to make that 1000% worse for them. But hopefully over time, we all adapt together and end up better off in the long run.

I read the article, I read the AI's verdict, I read the comments here, and I still don't know if OP does or does not have a tear in their tendon!

The AI doesn't present evidence I can understand, it doesn't even present a plausible explanation why someone could conclude it is a tear.

The main things that made OP suspicious are the possibly unnecessary shockwave therapy. Which seems harmless. And using a homeopathic gel that I would classify as more of a herbal medicine because it contains several ingredients I know people use for shoulder pain, and some even in concentrations that might even have an effect.

If this is the best rebuttal AI can come up with I would trust the diagnosis. But then OP never trusted the diagnosis and now they have several they cannot.

I wonder what this article would have concluded if the author considered how many individuals of the HN readership were professional radiologists.

Word of caution, I used Claude to read my MRI images too.

Looked legit.

Until I really dug in, and found that all it did was read the embedded annotations.

DICOM is a container format after all.

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.

Trusting Claude Code with my MRI before I trust it with my production database. Priorities.

Nice, I have Claude, now I just need an MRI (which in some countries is sort of a hard requirement still unfortunately, long queues)

I had Claude interpret a photo of the heart monitor when I was in the ER last year. It said I was about to die. I was fine.

You can try sending basic chest radiographs to GPT and it'll fail at interpretation. I'd be wary of premature conclusions.

Its very interesting how people trust LLMs in domains they know little about.

Instead, it is my experiences with LLMs in a domain that I know very well that makes me skeptical of their performance across the board. I find issues in code review multiple times a day with their output, and they are explicitly and extensively trained on this use-case, unlike with the MRI data. Sometimes I veer into other domains I have decent knowledge about (construction, carpentry, landscaping) and LLMs disappoint me there as well.

I suppose Gell-Mann amnesia is a universal human quirk and not restricted to just the news.

I love how the doctors injected basically water. I imagine the doctor thinking "we did all we could"

The text on this is unreadable on my machine because the background immediately goes to white.

This is like someone not knowing software development at all doing a code review.

Here's an example that illustrates a shortcoming about how medicine has historically been practiced and how it might change with the advent of AI.

A person very familiar with me was having an interaction at a review board level at Stanford. They had this rare illness that they were treating and someone had the "bright idea" of suggesting of saying ... "hey, why don't we look at the ten other times we treated this exact illness and see what worked!" Everyone was delighted with this novel idea (discussion circa 2021). My person was a bit disgusted as this is simple feedback loop style improvement and WTF! they should be doing this all the time to get probabilistic style suggestions for many treatments. I know it happens within certain healthcare systems (e.g., Kaiser had full EMR back in early 2000s and saw right away that VIOXX was killing people. So, they stop prescribing it. citation: Kaiser panel member paraphrase at a healthcare conference in 2010). If you just observe the healthcare system, you can see that the healthcare systems and most EMRs don't typically capture the feedback loop (i.e, when's the last time a doctor followed up and said "did you feel better after the last treatment?" or measures the result.) AI itself can't solve this as it doesn't have access to the data feedback loop. However, maybe AI's within the EMR will help "suggest" evidence based treatments. I could go on and on, but as a math guy, I've often been shocked at the non-evidence based assertions some doctors make. My conclusion is that if you're not "in the fairway", they are typically just guessing.

I've found ChatGPT to be much better at medicine than doctors. For example, every winter, I would get itchy toes. I was quite concerned because they could be quite painful. But the symptoms were not obvious and they wouldn't occur often. The toes would swell up and become quite red and uncomfortable. One doctor suggested gout, which was not the right diagnosis, because I have no urea problems. Others suggested a skin cream.

No... I told ChatGPT exactly what I told you and it came up with the answer: Chillblains, which should have been obvious given everything I described, yet general practitioners were clueless and often reached for high intervention approaches

Harmless condition fixed by wearing socks. I brought it up with the same GPs who had misdiagnosed me and none had heard of it.

Of course, I'm cognizant that it could be mistaken, but a hospital fed my diabetic aunt a normal sugar diet while she was in a coma and forgot to give her metformin, so I mean, it's not like humans can't be retarded as well. The difference is no one gets offended when I point out ChatGPT has the capacity to be an idiot. Instead they just fix it.

the more awesome thing to me is that you can run the MRI through an ensemble of LLMs and check to see if they converge among each other

I'm seeing surprisingly few comments about OP getting homeopathic treatment

I have had terrible experiences with medical professionals. Especially the experienced/senior/specialists. First, they just don't have the time to do a thorough research of my medical history. Second, they are often arrogant and resistant to any kind of critical questions. They have an apparently unwavering belief that they are correct. In fairness, they probably usually are, but they are not infallible, and they are at their weakest when it comes to the edge cases.

AI is completely without ego, and can process all my medical records in minutes. In truth, even today, I would rather have an AI analyse my records.

If you have 2 clocks you have none.

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.

I used my dog to clean my room.

I asked a bird about my father's potential prostate cancer. It gave extremely good advice.

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.

> There's something incredibly peaceful about being in the hands of an expert you trust.

I want to know if this is a religious thing, or is related to never having had multiple doctors so bad it seemed like they were actively trying to kill you, or both. I've never had this peaceful experience personally within the realm of healthcare.

> AI can absolutely shatter that feeling in an uncomfortable way

Good. Reality is always good.

> but I don't know if I can fully trust AI either.

WTF??!? Why on earth would anybody ever think they could fully trust LLMs? Even their most vocal proponents concede they aren't infallible panaceas.

I have already done that several times, and I found the comments from ChatGTP/Claude, is absolutely bullshit.

Fucking doctor google bullshit, they want medical treatment but don't want medical 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.