HACKER Q&A
📣 narogab

ML, DNN and Creativity in Battle vs. Covid-19?


Everything I see about Covid-19/coronavirus is old-school standard statistics - no ML, no DNNs. Doctors and statisticians screaming and warning to not do X unless we have proven X effective with classically statistically-controlled studies (which they confess, will take months to complete, write up, peer review and publish in the journal of their choice). But when we look around, having done over the last 5 decades literally tens of thousands of such studies, none of them seems to have any relevance!

Seems the medical community thinks success against Covid-19 can only be achieved with more masks, more gloves, more hospitals, more randomly-selected controlled double-blind studies and particularly more money for a (bigger) medical community.

I hate to be critical of the very people who are doing so much work, but I am sorely pressed to see how the group of dullards in charge (and I mean the entire medical and drug community) can possibly come up with a solution.

Example: look at this - this is a solution from the boneheads in charge:

https://www.jpost.com/International/Israeli-doctor-in-Italy-We-no-longer-help-those-over-60-621856

"Let the old and weak die! " What a novel solution!

Seriously, WTF happened to creativity? Where are the ML and DNN people? Where's the "artificial intelligence" (b/c there apparently isn't enough of the real thing to solve this problem. Why isn't more of the work done to date useful in finding solutions? Medical "science" has let us down.


  👤 rvz Accepted Answer ✓
The current tools that are used in clinical environments have been tested and proven to be safe for many years and are also compliant with healthcare regulations to ensure that they are safe to use because it involves human life.

You mention Machine Learning or Deep Learning based solutions are not used more to tackle the COVID-19 outbreak. The problem with using them is that the explainability in its decision-making is very poor and is as transparent as a blackbox at best. Thus it isn't useful for a clinician to give an explanation why this 'AI' came to that decision, which is very unsafe in a medical environment.

Explainable tools like decision support systems are what medical professional favour over the hype of DNNs, neural nets, or other AI buzzwords these days.


👤 tastroder
(Vouching since this might be a good discussion to have.)

> I see about Covid-19/coronavirus is old-school standard statistics - no ML, no DNNs.

What you call "old-school" is also proven. The biomedical domain uses these models because they understand how they work, what abstractions went into them, and when they are reliable methods to lean on. Machine learning and DNNs are pretty useless without a specific task and good datasets (add large to that list for DNNs), very much like wet trials in the medical field.

If you look at the biomedical field in the last few months, lots of efforts already come together here that you might appreciate. Peer reviews of relevant papers are expedited, results are digitally disseminated around the world, cases are tracked with pretty unprecedented speed across bureaucratic borders.

> Seriously, WTF happened to creativity? Where are the ML and DNN people?

Where they belong. Some help people in the field, others focus on their own research, some will definitely try to put their specific methods to the test in order to facilitate other efforts.

I realize that many people these days want to help but please, this is not the time to get your covid paper on arxiv just because. Just like we should call out people profiteering from this pandemic economically, we should strive against adding pure noise. Note that this shouldn't hinder creativity but that is a completely separate thing. If you have a great idea to help, go ahead.

> Where's the "artificial intelligence" (b/c there apparently isn't enough of the real thing to solve this problem. Why isn't more of the work done to date useful in finding solutions? Medical "science" has let us down.

Medical science is doing what they can, the presumption that a buzzword can do it better than people that dedicate their life to this is neither help-, nor respectful.