AI predicts certain esophageal and stomach cancers three years before diagnosis

It's deep in the 'just statistics' territory of ML/AI by the sounds of it, yeah. This is just a classification problem (cancer, not cancer) with a bunch of available patient data spanning different dimensions, four of them known risk factors, and regression analysis to find others (well, re-discovering/confirming those four too) that correlate.

I imagine at least the title here is a groan for the paper authors.

That is machine learning or more colloquially: AI. A pretty cool result regardless.

Accuracy is well understood to be a terrible, misleading metric and any reputable report would strive to avoid emphasizing its importance.

For those curious their test set AUC appears to be 77.

Maybe I’m misunderstanding, but if you could have a test that doesn’t say anything if it isn’t sure, but if it is sure with very high confidence gives you a true positive, that has a lot of value.

Even with an accuracy score, it’s meaningless. Accuracy isn’t the right metric.

Add smoking as a risk factor, in addition to high sodium in diets. This is especially the case in asian countries [0].

[0]https://www.nature.com/articles/s41598-022-10014-4

My dad had esophageal cancer and until he was diagnosed with stage 4 with multiple metastases he didn't really have symptoms. He'd had a lower appetite and lost weight in the months leading up to his diagnosis, but thought that was just lifestyle and diet changes finally clicking. Esophageal cancer with multiple metastases is usually fatal at about four months after diagnosis (my dad died at 3.5 months after diagnosis).

But you don't go from no cancer to dead in 4 months, the cancer is there for years. This research is finding signals from blood tests that correlate to cancer long before it has visible effects. The trigger event you're theorizing is just cancer at a lower level

Most likely the last one. As I understand it, our diagnosis techniques for cancer are very limited and basically only at the “omg, that’s obviously cancer” phase of progression (ie it has to be noticeable so that we can do a biopsy). Even our imaging techniques are limited because surgeries can discover that the cancer is worse than what was originally thought. In some cases we can catch the cancer very early, but even in those cases it’s a mixture of luck and we don’t actually know how long the cancer was actually growing for (“early” just means early enough for treatment to be very effective).

At least that’s my external highly amateur understanding of the situation.

Wouldn’t it be closer to eating the mega burger regularly, like every week? In which case if you have that habit, it could easily be predicted that you would continue.

But the actual model seems simpler, measuring something like the obesity from your mega burger habit.

While paper is paywalled, it doesn’t sound that sophisticated.

The blurb mentions the prediction requires a couple of measurements that aren’t usually taken like stomach and waist circumference.

From my experience with building models (in other domains), the key to break through is very often new data that previously wasn’t considered as it wasn’t easily available.

I’m not sure what the point of this comment is. Nobody thinks this is how stomach cancer works.

A hiatal hernia or eosinophilic esophagitis come to mind. The latter more likely if you have allergies (e.g. hay fever).

You could get a proton pump inhibitor to lower stomach acid production, and/or make sure not to eat too close to bed time.

Have it checked out again, and consider getting a second opinion.

> So what this AI tool does is make it safer to be obese, thereby causing long-term suffering for more of the population. And part of the reason why people are obese is because of technology doing so many things so efficiently for them.

What? How does that make sense? It's easier to be obese because now you won't die from cancer, therefor people will stay obese? I guess that's technically true but like... the alternative is they get cancer.

If the assumption is "well, they'll get cancer and then they'll have a wake up call and lose weight, assuming they survive" I question how that's better than "they'll get a cancer diagnosis, very likely survive, and still understand the severity of their issue".

I think you're also assuming that overweight people aren't aware of the problem. Anyone who's going to the dr and is overweight is going to be told flat out that they need to lose the weight to improve their health. Yes, it would be great to have some way to just not be overweight but I don't see how this research is making things worse.

It just seems like this allows earlier detection of the possibility of getting cancer, which surely means more opportunity to tell the patient to lose weight. By the time you've got stomach cancer, it's a little late.

(Obesity still seems to be the major factor in the new test -- the old one required hip and waist measurements, and the new one does not, which says to me that they've found a bunch of correlates to obesity which don't require taking new measurements.)

> How about instead of developing more technology, we address the root problems instead?

That's not a business plan. Panem et circenses, nothing changed since then, it's planned and there is no problem to fix.

Obesity isn't a cause. Metabolic syndrome usually leads to obesity, and metabolic syndrome is the driver behind cancers. https://www.youtube.com/watch?v=dBnniua6-oM

My guess is in cases like this it comes from collective real-world past experiences (in either AI or biomedical research or both) of what's going on behind the scenes, leading to skepticism about claims.

For what it's worth it doesn't seem depressing to me, it's more like holding it up to a standard that guarantees real-world utility. It's also depressing to see misleading claims being used to further academic careers at the expense of patients and investors.

I think you're right to question whether skepticism goes too far, but I don't necessarily see skepticism as a negative thing. If it holds up to places like HN skeptic corners it probably will hold up everywhere.

We can't be #1 at anything. I would assume a depression support forum would be worse.

“When early detection occurs, patients can take additional steps to help prevent cancer.”

Blurb doesn’t say what those are. Paper is paywalled.

The extra data points as inputs into the prediction are things like waist and stomach measurement. So suspect one thing is weight loss.

something something nexus telegram