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

antoine.fi

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

#6

Post by sxg »

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.

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

#8

Post by amluto »

maxall4 wrote: post #3
Aeolun wrote: post #2

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

Especially an MRI which is a 3D medium —something current LLMs are very bad at.

I know little about radiology, but MRI is a 3D medium. I would not be at all surprised if one could slice an MRI the wrong way to produce a 2D image that fails to show a feature that exists in the source data.

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

#9

Post by TSiege »

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.

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