[tqi]

> This makes it hard to predict when and how deep learning methods will fail (there are no theoretical guarantees that deep learning will work).

I actually think we know fairly well how deep learning methods work (and what the shortcomings are), we just have no way to interpret the models it produces. Wouldn't ML techniques to reduce scan times fail at the most critical moments, ie when patients had unusual or unexpected ailments? Using ML in on downsampled MRI images feels akin to having an artist with a lot of familiarity of human anatomy touch up a scan.

[csee]

I speculate (and hope) that ML diagnostics will help give medical care access to really poor people in really poor countries. There's not enough cheap doctors to help all of them, and if ML can speed things up and reduce marginal costs to zero, even if it degrades quality of care, a lot of lives could be saved. 80% ML + 20% human is better than no medical care at all.

[jstx1]

Those countries are lacking basic healthcare standards and infrastructure. I doubt that lack of diagnosis due to understaffing is the bottleneck.

[randomluck040]

It often still is a good idea to have an approach for a possible second step for when the first step or steps are established. A lot of ifs and sometimes countries entirely skip kinds of technology like the landline phones in Africa and go to mobile phones directly since it was easier to establish. Maybe not-so-wealthy countries will see an entirely different kind of health care in 10 years than we know it now.

[csee]

Countries with a GDP per capita of $5,000-$10,000 typically do have good medical care in private, but most of the population is excluded because of cost. If we give the doctors ML tools to increase bandwidth, then that should help the situation by increasing supply. Suppose we could 10x the bandwidth for routine scans. The cost should go down in private, public health capacity will go up, and overall more people should be able to access it.

[exdsq]

The issue is training people to use the machines and keeping them running, not even the doctors themselves.

[csee]

That's true, but I don't see that as necessarily decisive. If 1 doctor and 1 engineer can achieve the bandwidth of 10 (more?) doctors on some specific scan, we're still talking about less intellectual capital and less training requirements overall.

Also I don't think we're talking about special hardware here. Couldn't we just have a software package produced by someone (university, company in a wealthier country) that is used by docs everywhere? Could be done without the need of a dedicated local engineer? Perhaps the WHO could approve certain software packages for universal use in very specific cases.

[moonchrome]

>80% ML + 20% human is better than no medical care at all.

That implies that doing something is always better than doing nothing. Unless we're talking things like antibiotics, I'm not sure I'd agree. Medical error is a nontrivial cause of death, increasing that significantly could probably be worse than what you're trying to treat.

[tangoed]

I'd argue that knowing fairly well and theoretical guarantees are significantly different.

As an example, you can run a million simulations on a satellite with different initial conditions to test your new control algorithm. However, you have infinitely many possible initial conditions, and you can't simulate all of them. If you however show that the closed loop system in stable sine sense, it's a more rigorous guarantee.

[bick_nyers]

Agreed. I work in medical imaging, and people in the industry are very weary of existing technology that does have theoretical guarantees. Upscaling via bicubic/lancoz, or lossy compression (even if it has guaranteed 0.99 SSIM or NCC). Then they go ahead and do reads on 512x512 pixel CT scans. Even with a theoretical guarantee on bounded error ranges, you still have the cultural perception problem to deal with. Only if the improvements from a feature perspective are an order of magnitude better will it see any adoption imo.

[HPsquared]

Whether that is acceptable or not depends on the purpose of the scan. If it's for a routine and defined purpose, like measuring the size of something, a bit of artistic licence by the computer is not too bad, I think. As long as it gets the size right (or whatever specific aspect is relevant)