3 ms·

I remember talking to a radiologist who said he was sure something like this was coming like ten years ago where instead of a radiologist looking at scans manua

by pooper 3y ago

I remember talking to a radiologist who said he was sure something like this was coming like ten years ago where instead of a radiologist looking at scans manually, a machine would go through a lot of images and flag some for manual review. We haven't even gotten there yet, have we?

matheusd 3y ago
Maybe it's a liability issue, not a competency issue.
dagw 3y ago
We haven't even gotten there yet, have we? Yes and no. Countless teams have solved exactly this problems at universities and research groups across the world. Technically it's pretty much a solved problem. The hard part is getting the systems out of the labs and certified as an actual product and convincing hospitals and doctors to actually use them.
osrec 3y ago
Yes, we absolutely are there: https://youtu.be/D3oRN5JNMWs?feature=shared https://youtu.be/D3oRN5JNMWs?feature=shared My professor (Sir Michael Brady) at university 14 years ago set up a company to do this very thing, and he already had reliable models back before 2010. I believe their company was called Oxford Imaging or something similar.
- wruza 3y ago
  Yep, everyone seems to forget that ML was available before 2021. Had a conversation recently with my former colleague who learned about some plastic packaging company which used "AI" to predict client orders and inform them about scheduling implications. When I told him that you don't need Transformers and 30GB models for that, he was quasi-confused, cause he kinda knew it but the hype just overtook his knowledge.
  - anon373839 3y ago
    In ML courses, you’re taught to try simpler methods and models before turning to more complex ones. I think that’s something that hasn’t made it into the mainstream yet. A lot of people seem to be using GPT-4 for tasks like text classification and NER, and they’d be much better off fine-tuning a BERT model instead. In vision, too, transformers are great but a lot of times, a CNN is all you really need.

by pooper 3y ago

matheusd 3y ago

Maybe it's a liability issue, not a competency issue.

dagw 3y ago

We haven't even gotten there yet, have we? Yes and no. Countless teams have solved exactly this problems at universities and research groups across the world. Technically it's pretty much a solved problem. The hard part is getting the systems out of the labs and certified as an actual product and convincing hospitals and doctors to actually use them.

osrec 3y ago

Yes, we absolutely are there: https://youtu.be/D3oRN5JNMWs?feature=shared https://youtu.be/D3oRN5JNMWs?feature=shared My professor (Sir Michael Brady) at university 14 years ago set up a company to do this very thing, and he already had reliable models back before 2010. I believe their company was called Oxford Imaging or something similar.

wruza 3y ago
Yep, everyone seems to forget that ML was available before 2021. Had a conversation recently with my former colleague who learned about some plastic packaging company which used "AI" to predict client orders and inform them about scheduling implications. When I told him that you don't need Transformers and 30GB models for that, he was quasi-confused, cause he kinda knew it but the hype just overtook his knowledge.
- anon373839 3y ago
  In ML courses, you’re taught to try simpler methods and models before turning to more complex ones. I think that’s something that hasn’t made it into the mainstream yet. A lot of people seem to be using GPT-4 for tasks like text classification and NER, and they’d be much better off fine-tuning a BERT model instead. In vision, too, transformers are great but a lot of times, a CNN is all you really need.