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Discussion (21 Comments)Read Original on HackerNews

plaidfujiabout 15 hours ago
It is 2026. How are we still publishing articles on medical diagnostics data science and using area under the ROC curve as the primary metric of success. ROC-AUC of 0.9 under severe class imbalance (almost always the case in diagnostics) could still mean something like 4/5 predicted diagnoses are wrong (false positives). Precision-Recall curve + mAP or GTFO.

Science article in question: https://www.science.org/doi/abs/10.1126/science.aec6129

Also, the most interesting result here is that the CNN-based feature encoder significantly outperformed a vision transformer encoder backbone…

steve-atx-7600about 10 hours ago
Teaching students how to interpret evidence must be way undervalued still. I went to one of the top CS schools 20 years ago and you could get a degree without even taking a single probability or stats class of any kind.
chrisjjabout 14 hours ago
> How are we still publishing articles on medical diagnostics data science and using area under the ROC curve as the primary metric of success.

Waste avoidance.

Bullsh*t is more than sufficient to convince an AI-gulled target audience.

Zaraif13about 13 hours ago
I don't agree with the flak Chinese labs get. If it's really that easy to distill and compete with frontier models, why aren't other countries anywhere near this AI race?
felixgalloabout 11 hours ago
Because distillation is a friendly term for industrial espionage, and most other countries are not willing to become international pariahs in the eyes of the west.
yogthosabout 7 hours ago
ElProlactinabout 24 hours ago
I much prefer Gemini. It tells me I'm very smart and almost always right.
vrighterabout 16 hours ago
you hit the nail right on the head!
t0bia_sabout 23 hours ago
I'm wonder when there will be model for predict future. Could be named "Crystal bAill"
mdp2021about 22 hours ago
> model [to] predict future

The attempt is already there: "predicting the future" is called "intelligence".

pizzlyabout 22 hours ago
Isn't detecting cancer predicting a possible future? Hopefully one you can change.
westurner1 day ago
From https://news.ycombinator.com/item?id=44693991 :

> EPS3.9 also had significant anti-tumor effects in the mice with liver cancer and activated anti-tumor immune responses

“A Novel Exopolysaccharide, Highly Prevalent in Marine Spongiibacter, Triggers Pyroptosis to Exhibit Potent Anticancer Effects” (2025) DOI: 10.1096/fj.202500412R https://faseb.onlinelibrary.wiley.com/doi/10.1096/fj.2025004...

"A Gemma model helped discover a new potential cancer therapy pathway" https://news.ycombinator.com/item?id=45604231 :

> eCPMV VNPs + EPS3.9 + [...]

"Scientists are discovering a powerful new way to prevent cancer" https://news.ycombinator.com/item?id=45474404

Notes re: Kidneys not Livers: https://news.ycombinator.com/item?id=47460486 ; gh/topic/healthcare-ai

K0balt1 day ago
Anyone know how many parameters?
westurner1 day ago
ScholarlyArticle: "Large-scale AI-guided liver malignancy diagnosis: multicenter study and a single-arm trial" (2026) Nature Medicine https://www.nature.com/articles/s41591-026-04589-y

Source: https://github.com/alibaba-damo-academy/damo-radar

Model: https://huggingface.co/radar-generalist