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AI models that predict disease are not as accurate as reports might suggest

scientificamerican.com

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Re: AI models that predict disease are not as accurate as reports might suggest

#2
While the notion of treating these systems as “sociotechical” rather than purely technical is probably a good move wrt actually improving people’s lives, I can say from my own experience in academia that there are still way too many academics working in this field who don’t think it’s their problem. I’ve personally raised these types of issues before and been told “we’re computer scientists, not social scientists”, as if “social scientist” is a derogatory term. The biggest impediment here is, in my opinion, overcoming the bloated egos of the people who think the social impacts of their work are somehow out of scope. All is well as long as you can continue to publish.

Re: AI models that predict disease are not as accurate as reports might suggest

#3

While the notion of treating these systems as “sociotechical” rather than purely technical is probably a good move wrt actually improving people’s lives, I can say from my own experience in academia that there are still way too many academics working in this field who don’t think it’s their problem. I’ve personally raised these types of issues before and been told “we’re computer scientists, not social scientists”, a…

Preach.

There are way too many people that conflate MSE or other abstract technical measurements of model performance like they actually represent the impact any model has on a problem. Even if we could somehow perfectly predict an actual realization instead of a conditional expectation that still forgets to ask the question of why we predicted that. Are we exploiting systemic biases, like historically racist policies? Almost definitely (unless we've consciously tried to adjust for them, and still we've probably done that incorrectly). I've become much less interested in models that basically just interpolate (very well I might add), and more in frameworks that attempt to answer why we see particular patterns.

Re: AI models that predict disease are not as accurate as reports might suggest

#4
Color me, personally, surprised. Between publication bias and the general public ignorance of AI and its evolving capabilities, and over a decade of results in AI health being overblown before transformers, how could we have predicted that post-transformer results in AI health would continue to be overblown?

Re: AI models that predict disease are not as accurate as reports might suggest

#5
Not that surprising. AI learning seems to do best with fairly predictable systems, and when it comes to individual outcomes in medicine, there's a lot of mystery involved. A group of people with similar genetic makeup and exposure history to carcinogens or pathogens won't all respond identically - some get persistent cancers, some get nasty infections, and some don't.

For example, training an AI on historical tidal data would likely lead to very good future tide timing and height predictions, without any explicit mechanistic model needed. Tides have high predictability and relatively low variability (things like unusual wind patterns accounting for most of that).

In contrast, there are some current efforts to forecast earthquakes by training an AI on historical seismograph data, but whether or not these will be of much use is similarly questionable.

https://sciencetrends.com/ai-algorithms-being-used-to-improv...

Re: AI models that predict disease are not as accurate as reports might suggest

#6
Yet.

One thing media consistently gets wrong is the rate of innovation that is happening. Media also doesn't have access to state-of-the-art models, only from the trigger-happy startups too eager to release half-baked version.

It's akin to downloading Image Generation tools from the App Store and concluding that's state of the art

Re: AI models that predict disease are not as accurate as reports might suggest

#7
As someone who works in healthcare, so much of what I read about AI makes me think that the people who are enthusiastic about healthcare AI don't have much experience doing it.

The scenarios rarely seem to fit with what I'm actually practicing. Most of medicine is boring, it is largely routine, and if we don't know what's going on, it's because we're not the right person to be managing the patient. Most of my time is spent talking to people - patients, colleagues, family. I explain the diagnosis, I talk about the plan, I am getting ideas of what the patient wants and values, and then actioning it. I spend very little of my time like Dr House pondering what the next most important test to perform is for a patient who is confounding us.

Re: AI models that predict disease are not as accurate as reports might suggest

#8
I recently published a paper, where we explain how an FDA approved prediction model, build into a widely used cardiac monitor was developed with an incredibly biased method.

https://doi.org/10.1097/ALN.0000000000004320

Basically, the training and validation data was engineered so an important range for one of the predictor variables was only present in one of the outcomes, making perfect prediction possible for these cases.

I summarize the paper in this Twitter thread: https://twitter.com/JohsEnevoldsen/status/156164115389992960...

Re: AI models that predict disease are not as accurate as reports might suggest

#9
post #7

As someone who works in healthcare, so much of what I read about AI makes me think that the people who are enthusiastic about healthcare AI don't have much experience doing it. The scenarios rarely seem to fit with what I'm actually practicing. Most of medicine is boring, it is largely routine, and if we don't know what's going on, it's because we're not the right person to be managing the patient. Most of my time is…

That scenario sounds like it lends itself more to AI automation than a Dr. House type one.

Re: AI models that predict disease are not as accurate as reports might suggest

#10
post #6

Yet. One thing media consistently gets wrong is the rate of innovation that is happening. Media also doesn't have access to state-of-the-art models, only from the trigger-happy startups too eager to release half-baked version. It's akin to downloading Image Generation tools from the App Store and concluding that's state of the art

It baffles me that people can watch the trendline of

"Job X can be automated in 40 years" (5 years ago)

"Job X can be automated in 10 years" (2 years ago)

"Job X can be automated in 5 years" (1 week ago)

And feel comfortable poking holes in the AI models, pointing out where it fails. Obviously? But nobody 3 years ago thought that graphic design or creative writing was on death's row either.

You have to spend a modicum of effort looking at how predictions have evolved over the past couple years, but once you do, it's very clear that mocking current AI systems makes you look like a clown.

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