[DrScientist]

But in your scenario - which part is adding the value?

Your deep multimodal models or the MRI imaging?

What you are essentially saying is the signal is so subtle that only a large NN can reliably extract it.

While that may well be the case, it would be better to have a scan/diagnostic that doesn't need that level of signal processing to interpret.

For example - you don't need a large generative deep multimodal model to read a Covid antigen or PCR test.

[whimsicalism]

There are tons & tons of conditions that do not have easy scans/diagnostic and rely on subtle signals - especially if they are not a binary yes/no but a regression style prediction.

We've picked a lot of the low-hanging simple to extract signals, we need large models to go to the next phase for things like parkinsons, etc.

[DrScientist]

I'm not saying there isn't stuff that can't be done more reliably - but I'd argue long term might be better investing in getting better data - rather than better fishing in a pool of low quality data.