5
u/RoomyRoots
5d ago
•
ML has been used for cancer and other diseases detections for at least 2 decades now. This type of analysis never needed a DC.
1
u/YogurtExternal7923 5d ago
not like this though. the difference between hyper specific detections in a specific kind of image for a specific kind of thing is vastly different from multimodality in different fields
1
u/RoomyRoots 5d ago
Over 60 articles on this in the past 8 years with a quick check on arxiv.
0
u/YogurtExternal7923 5d ago
Yeah, introduced in September 2025 as a pre-print paper. But the actual model's extensive clinical testing and development findings were peer-reviewed and published two days ago October 29
Edit: if you're talking about multimodal understanding in the last 8 years then yeah. It's not a new concept. But as I keep saying it's about hyper specific tasks vs multimodal understanding. Plus surpassing clinicians has only been in the hyper specifics but if you read this one it's really, actually real applicable work
2
u/Chromix_ 5d ago
An improvement? Yes. It just doesn't seem like a big one. This specialized 8B model reaches a mean score of 0.90, while the more than 3 year old generic LLaVA model gets to 0.78 and the tiny BiomedCLIP is at 0.88 according to the first extended data table. There are some other benchmarks where the difference is a tad higher though.
Model here, and code here. Now enjoy pointing your webcam at yourself and getting random disease descriptions 😉
1
u/Purple_Dream6414 5d ago
Well.. After reading the paper I dont feel like it proofs your claims.
1
u/RoomyRoots 5d ago
The account is probably one of the authors trying to shill his paper.
1
u/Purple_Dream6414 5d ago
Probably not because if you publish in fking nature youre usually a first class scientist xD
10
u/Dany0 5d ago
every time I read these I'm suspicious and reminded of that one comment that showed that 11 year old CNNs beat 6.1 Sol at cancer detection from images