alt Hacker NewsI'm not a medical researcher, but I am a computer guy; I was struck by something very different in the papers - the abstracts at least refer to "AI CAD" as what they're testing - no software information, no versioning - on the CS side, this stuff is of paramount importance to make sure we know how the software performs.
On the medical side, we need statistically significant tests that physicians can know and rely on - this paper was likely obsolete when it was published, depending on what "AI CAD" means in practice.
I think this impedance mismatch between disciplines is pretty interesting; any thoughts from someone who understands the med side better?
The link is essentially a press release. The information you want is (sorta) in the actual paper it describes *.
"The images were analyzed using a commercially available AI-CAD system (Lunit INSIGHT MMG, version 1.1.7.0; Lunit Inc.), developed with deep convolutional neural networks and validated in multinational studies [1, 4]."
It's presumably a proprietary model, so you're not going to get a lot more information about it, but it's also one that's currently deployed in clinics, so...it's arguably a better comparison than a SOTA model some lab dumped on GitHub. I'd add that the post headline is also missing the point of the article: many of the missed cases can be detected with a different form of imaging. It's not really meant to be a model shoot-out style paper.
* Kim, J. Y., Kim, J. J., Lee, H. J., Hwangbo, L., Song, Y. S., Lee, J. W., Lee, N. K., Hong, S. B., & Kim, S. (2025). Added value of diffusion-weighted imaging in detecting breast cancer missed by artificial intelligence-based mammography. La Radiologia medica, 10.1007/s11547-025-02161-1. Advance online publication. https://doi.org/10.1007/s11547-025-02161