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You can see it in just this PDF report.

It's multiple things. It never shows the subscapularis in the way that people actually look the tendon. It hyper fixates on the axial when I find the sagittal much more useful for subscapularis.

Figure 7. There's an arrow pointing "to the acromial undersurface". The arrow is not pointed to that location.

Figure 5. "thin bursal fluid". This is within physiologic variation, but is calling bursitis.

It keeps bringing up irrelevant normal things like the shape of the coracromipal arch, I assume because lots of websites have information about that as a patient focused possible cause for rotator cuff impingement.

I am reminded of the recent Stanford MIRAGE study which found that LLMs will happily hallucinate answers about medical images if the medical images are omitted.

https://arxiv.org/html/2603.21687v2



I don't understand why this is still confusing to people. The second "L" in LLM is language; these things are AWESOME at producing things that SOUND like language, including code. They have so much training data that it is almost always grammatically correct, and often makes sense. Extending this, it has obviously been trained on data containing phrases like "acromial undersurface" and "thin bursal fluid", and "coracromipal arch", in the context of shoulder injury and related imaging. BUT IT DOES NOT KNOW HOW TO DIAGNOSE ANYTHING. So, it SOUNDS like a radiologist or specialist, and might be in the ballpark of correct-ish-ness, but ultimately is a fancy Markov model.


lol yea I wasn’t going to put in a full dictation on the internet but clearly a lot of misinterpretations from the AI




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