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Using AI for anomaly detection is nothing new though. Haven’t read any article about this specific ‘discovery’ but usually this uses a completely different technique than the AI that comes to mind when people think of AI these days.
That’s why I hate the term AI. Say it is a predictive llm or a pattern recognition model.
Say it is a predictive llm
According to the paper cited by the article OP posted, there is no LLM in the model. If I read it correctly, the paper says that it uses PyTorch’s implementation of ResNet18, a deep convolutional neural network that isn’t specifically designed to work on text. So this term would be inaccurate.
or a pattern recognition model.
Much better term IMO, especially since it uses a convolutional network. But since the article is a news publication, not a serious academic paper, the author knows the term “AI” gets clicks and positive impressions (which is what their job actually is) and we wouldn’t be here talking about it.
That performance curve seems terrible for any practical use.
Yeah that’s an unacceptably low ROC curve for a medical usecase
Well, this is very much an application of AI… Having more examples of recent AI development that aren’t ‘chatgpt’(/transformers-based) is probably a good thing.
it’s a good term, it refers to lots of thinks. there are many terms like that.
it refers to lots of thinks
So it’s a bad term.
It’s literally the name of the field of study. Chances are this uses the same thing as LLMs. Aka a neutral network, which are some of the oldest AIs around.
It refers to anything that simulates intelligence. They are using the correct word. People just misunderstand it.
the word program refers to even more things and no one says it’s a bad word.
Citation please?
Why do I still have to work my boring job while AI gets to create art and look at boobs?
Because life is suffering and machines dream of electric sheeps.
I dream of boobs.
Yes, this is “how it was supposed to be used for”.
The sentence construction quality these days in in freefall.
shrugs you know people have been confidently making these kinds of statements… since written language was invented? I bet the first person who developed written language did it to complain about how this generation of kids don’t know how to write a proper sentence.
What is in freefall is the economy for the middle and working class and basic idea that artists and writers should be compensated, period. What has released us into freefall is that making art and crafting words are shit on by society as not a respectable job worth being paid a living wage for.
There are a terrifying amount of good writers out there, more than there have ever been, both in total number AND per capita.
This isn’t a creative writing project. This isn’t an artist presenting their work. What in the world did that tangent even come from?
This is just plain speech, written objectively incorrectly.
But go on, I’m sure next I’ll be accused of all the problems of the writing industry or something.
Ironically, if they’d used an LLM, it would have corrected their writing.
Lmao
Sure, I definitely overreacted and I honestly was pretty stressed out the day I replied so yeah, fair. I think I have a point, this just wasn’t the salient place for it and I was too tired to realize that in the moment.
Objectively incorrect according to, who exactly?
Bro, it’s Twitter
And that excuses it I guess.
That would be correct, yes.
Twitter: Where wrongness gathers and imagines itself to be right.
Now make mammograms not $500 and not have a 6 month waiting time and make them available for women under 40. Then this’ll be a useful breakthrough
It’s already this way in most of the world.
Oh for sure. I only meant in the US where MIT is located. But it’s already a useful breakthrough for everyone in civilized countries
For reference here in Australia my wife has been asking to get mammograms for years now (in her 30s) and she keeps getting told she’s too young because she doesn’t have a familial history. That issue is a bit pervasive in countries other than the US.
Better yet, give us something better to do about the cancer than slash, burn, poison. Something that’s less traumatic on the rest of the person, especially in light of the possibility of false positives.
Unfortunately AI models like this one often never make it to the clinic. The model could be impressive enough to identify 100% of cases that will develop breast cancer. However if it has a false positive rate of say 5% it’s use may actually create more harm than it intends to prevent.
Another big thing to note, we recently had a different but VERY similar headline about finding typhoid early and was able to point it out more accurately than doctors could.
But when they examined the AI to see what it was doing, it turns out that it was weighing the specs of the machine being used to do the scan… An older machine means the area was likely poorer and therefore more likely to have typhoid. The AI wasn’t pointing out if someone had Typhoid it was just telling you if they were in a rich area or not.
That’s actually really smart. But that info wasn’t given to doctors examining the scan, so it’s not a fair comparison. It’s a valid diagnostic technique to focus on the particular problems in the local area.
“When you hear hoofbeats, think horses not zebras” (outside of Africa)
That’s why these systems should never be used as the sole decision makers, but instead work as a tool to help the professionals make better decisions.
Keep the human in the loop!
Not at all, in this case.
A false positive of even 50% can mean telling the patient “they are at a higher risk of developing breast cancer and should get screened every 6 months instead of every year for the next 5 years”.
Keep in mind that women have about a 12% chance of getting breast cancer at some point in their lives. During the highest risk years its a 2 percent chamce per year, so a machine with a 50% false positive for a 5 year prediction would still only be telling like 15% of women to be screened more often.
This is a great use of tech. With that said I find that the lines are blurred between “AI” and Machine Learning.
Real Question: Other than the specific tuning of the recognition model, how is this really different from something like Facebook automatically tagging images of you and your friends? Instead of saying "Here’s a picture of Billy (maybe) " it’s saying, “Here’s a picture of some precancerous masses (maybe)”.
That tech has been around for a while (at least 15 years). I remember Picasa doing something similar as a desktop program on Windows.
I’ve been looking at the paper, some things about it:
- the paper and article are from 2021
- the model needs to be able to use optional data from age, family history, etc, but not be reliant on it
- it needs to combine information from multiple views
- it predicts risk for each year in the next 5 years
- it has to produce consistent results with different sensors and diverse patients
- its not the first model to do this, and it is more accurate than previous methods
Good stuff
Everything machine learning will be called “ai” from now until forever.
It’s like how all rc helicopters and planes are now “drones”
People en masse just can’t handle the nuance of language. They need a dumb word for everything that is remotely similar.
It’s because AI is the new buzzword that has replaced “machine learning” and “large language models”, it sounds a lot more sexy and futuristic.
Kinda mean of you calling Billy precancerous masses like that smh
I don’t care about mean but I would call it inaccurate. Billy is already cancerous, He’s mostly cancer. He’s a very dense, sour boy.
Serious question: is there a way to get access to medical imagery as a non-student? I would love to do some machine learning with it myself, as I see lot’s of potential in image analysis in general. 5 years ago I created a model that was able to spot certain types of ships based only on satellite imagery, which were not easily detectable by eye and ignoring the fact that one human cannot scan 15k images in one hour. Similar use case with medical imagery - seeing the things that are not yet detectable by human eyes.
This is similar to wat I did for my masters, except it was lung cancer.
Stuff like this is actually relatively easy to do, but the regulations you need to conform to and the testing you have to do first are extremely stringent. We had something that worked for like 95% of cases within a couple months, but it wasn’t until almost 2 years later they got to do their first actual trial.
The AI genie is out of the bottle and — as much as we complain — it isn’t going away; we need thoughtful legislation. AI is going to take my job? Fine, I guess? That sounds good, really. Can I have a guaranteed income to live on, because I still need to live? Can we tax the rich?
If it has just as low of a false negative rate as human-read mammograms, I see no issue. Feed it through the AI first before having a human check the positive results only. Save doctors’ time when the scan is so clean that even the AI doesn’t see anything fishy.
Alternatively, if it has a lower false positive rate, have doctors check the negative results only. If the AI sees something then it’s DEFINITELY worth a biopsy. Then have a human doctor check the negative readings just to make sure they don’t let anything that’s worth looking into go unnoticed.
Either way, as long as it isn’t worse than humans in both kinds of failures, it’s useful at saving medical resources.
an image recognition model like this is usually tuned specifically to have a very low false negative (well below human, often) in exchange for a high false positive rate (overly cautious about cancer)!
This is exactly what is being done. My eldest child is in a Ph. D. program for human - robot interaction and medical intervention, and has worked on image analysis systems in this field. They’re intended use is exactly that - a “first look” and “second look”. A first look to help catch the small, easily overlooked pre-tumors, and tentatively mark clear ones. A second look to be a safety net for tired, overworked, or outdated eyes.
And if we weren’t a big, broken mess of late stage capitalist hellscape, you or someone you know could have actually benefited from this.
Yea none of us are going to see the benefits. Tired of seeing articles of scientific advancement that I know will never trickle down to us peasants.
Our clinics are already using ai to clean up MRI images for easier and higher quality reads. We use ai on our cath lab table to provide a less noisy image at a much lower rad dose.
pretty sure iterate is the wrong word choice there
Dude needs to use AI to fix his fucking grammar.
Wanna bet it’s not “AI” ?
This seems exactly like what I would have referred to as AI before the pandemic. Specifically Deep Learning image processing. In terms of something you can buy off the shelf this is theoretically something the Cognex Vidi Red Tool could be used for. My experience with it is in packaging, but the base concept is the same.
Training a model requires loading images into the software and having a human mark them before having a very powerful CUDA GPU process all of that. Once the model has been trained it can usually be run on a fairly modest PC in comparison.
It’s probably more “AI” than the LLMs we’ve been plagued with. This sounds more like an application of machine learning, which is a hell of a lot more promising.
AI and machine learning are very similar (if not identical) things, just one has been turned into a marketing hype word a whole lot more than the other.
Machine learning is one of the many things that is referred to by “AI”, yes.
My thought is the term “AI” has been overused to uselessness, from the nested if statements that decide how video game enemies move to various kinds of machine learning to large language models.
So I’m personally going to avoid the term.
AI == Computer Thingy that looks kinda “smart” to people that don’t understand it. it’s like rectangles and squares. you should use the more precise word (CNN, LLM, Stable diffusion) when applicable, just like with rectangles and squares
Nooooooo you’re supposed to use AI for good things and not to use it to generate meme images.
I think you mean mammary images?
Ok, I’ll concede. Finally a good use for AI. Fuck cancer.
It’s got a decent chunk of good uses. It’s just that none of those are going to make anyone a huge ton of money, so they don’t have a hype cycle attached. I can’t wait until the grifters get out and the hype cycle falls away, so we can actually get back to using it for what it’s good at and not shoving it indiscriminately into everything.
Those are going to make a ton of money for a lot of people. Every 1% fuel efficiency gained, every second saved in an industrial process, it’s hundreds of millions of dollars.
You don’t need AI in your fridge or in your snickers, that will (hopefully) die off, but AI is not going away where it matters.
Those are going to make a ton of money for a lot of people.
Right, but not any one person. The people running the hype train want to be that one person, but the real uses just aren’t going to be something you can exclusively monetize.
Depends how you define “a ton” of money. Plenty of startups have been acquired for silly amounts of money, plenty of consultants are making bank, make executives are cashing big bonuses for successful improvements using AI…
I define “a ton” of money in this case to mean “the amount they think of when they get the dollar signs in their eyes.” People are cashing in on that delusion right now, but it’s not going to last.
Also, for GPU prices to come down. Right now the AI garbage is eating a lot of the GPU production, as well as wasting a ton of energy. It sucks. Right as the crypto stuff started dying out we got AI crap.
Yeah, fuck that detecting cancer crap, I want to game!
GPU price hikes are causing problems outside of the gaming industry, too. Imaging, scientific research, astronomy…
Might be, but I somehow don’t picture an astronomer complaining about GPU prices on lemmy…
There are actually a ton of people in research and academia on here.
Or at least there were. I don’t know what the current state of the Lemmy community is.
The hypesters and grifters do not prevent AI from being used for truly valuable things even now. In fact medical uses will be one of those things that WILL keep AI from just fading away.
Just look at those marketing wankers as a cherry on the top that you didn’t want or need.
The hypesters and grifters do not prevent AI from being used for truly valuable things even now.
I mean, yeah, except that the unnecessary applications are all the corporations are paying anyone to do these days. When the hype flies around like this, the C-suite starts trying to micromanage the product team’s roadmap. Once it dies down, they let us get back to work.
People just need to understand that the true medical uses are as tools for physicians, not “replacements” for physicians.
I think the vast majority of people understand that already. They don’t understand just what all those gadgets are for anyway. Medicine is largely a ''blackbox" or magical process anyway.
There are way too many techbros trying to push the idea of turning chat gpt into a physician replacement. After it “passed” the board exams, they immediately started hollering about how physicians are outdated and too expensive and we can just replace them with AI. What that ignores is the fact that the board exam is multiple choice and a massive portion of medical student evaluation is on the “art” side of medicine that involves taking the history and performing the physical exam that the question stem provides for the multiple choice questions.
And it has gone exactly nowhere either hasn’t it. Nor do those techbros want the legal and moral responsibilities that come with an actual licence to pass the boards.
I think there are some techbros out there with sleazy legal counsel that promises they can drench the thing in enough terms and conditions to relieve themselves of liability, similar to the way that WebMD does. Also, with healthcare access the way it is in America, there are plenty of people who will skim right past the disclaimer telling them to go see a real healthcare provider and just trust the “AI”. Additionally, there’s enough slimy NP professional groups pushing for unsupervised practice that they could just sign on their NP licenses for prescriptions, and the malpractice laws currently in place would be difficult to enforce depending on outcomes and jurisdictions.
This doesn’t get into the sowing of discord and discontent with physicians that is happening even without these products existing in the first place. Even the claims that an AI could potentially, maybe, someday sorta-kinda replace physicians makes people distrust and dislike physicians now.
Separately, I have some gullible classmates in medical school that I worry about quite a lot, because they’ve bought into the line that chat GPT passed the boards, so they take its’ hallucinations as gospel and argue with our professor’s explanations as to why the hallucination is wrong and the correct answer on a test is correct. I was not shy about admonishing them and forcefully explaining how these “generative AIs” are little more than glorified text predictors, but the allure of easy answers without having to dig for them and understand complex underlying principles is very alluring, so I don’t know if I actually got through to him or not.
A cure for cancer, if it can be literally nipped in the bud, seems like a possible money-maker to me.
That’s not what this is, though. This is early detection, which is awesome and super helpful, but way less game-changing than an actual cure.
It’s not a cure in itself, but isn’t early detection a good way to catch it early and in many cases kill it before it spreads?
It sure is. But this is basically just making something that already exists more reliable, not creating something new. Still important, but not as earth-shaking.
It’s a money saver, so it’s profit model is all wonky.
A hospital, as a business, will make more money treating cancer than it will doing a mammogram and having a computer identify issues for preventative treatment.
A hospital, as a place that helps people, will still want to use these scans widely because “ignoring preventative care to profit off long term treatment” is a bit too “mask off” even for the US healthcare system and doctors would quit.Insurance companies, however, would pay just shy of the cost of treatment to avoid paying for treatment.
So the cost will rise to be the cost of treatment times the incidence rate, scaled to the likelihood the scan catches something, plus system costs and staff costs.In a sane system, we’d pass a law saying capable facilities must provide preventative screenings at cost where there’s a reasonable chance the scan would provide meaningful information and have the government pay the bill. Everyone’s happy except people who view healthcare as an investment opportunity.
A hospital, as a business, will make more money treating cancer than it will doing a mammogram and having a computer identify issues for preventative treatment.
I believe this idea was generally debunked a little while ago; to wit, the profit margin on cancer care just isn’t as big (you have to pay a lot of doctors) as the profit margin on mammograms. Moreover, you’re less likely to actually get paid the later you identify it (because end-of-life care costs for the deceased tend to get settled rather than being paid).
I’ll come back and drop the article link here, if I can find it.
Oh interesting, I’d be happy to be wrong on that. :)
I figured they’d factor the staffing costs into what they charge the insurance, so it’d be more profit due to a higher fixed costs, longer treatment and some fixed percentage profit margin.
The estate costs thing is unfortunately an avenue I hadn’t considered. :/I still think it would be better if we removed the profit incentive entirely, but I’m pleased if the two interests are aligned if we have to have both.
Oh, absolutely. Absent a profit motive that pushes them toward what basically amounts to a protection scam, they’re left with good old fashioned price gouging. Even if interests are aligned, it’s still way more expensive than it should be. So yes, I agree that we should remove the profit incentive for healthcare.
Sadly, I can’t find the article. I’ll keep an eye out for it, though. I’m pretty sure I linked to it somewhere but I’m too terminally online to figure out where.
Honestly they should go back to calling useful applications ML (that is what it is) since AI is getting such a bad rap.
machine learning is a type of AI. scifi movies just misused the term and now the startups are riding the hype trains. AGI =/= AI. there’s lots of stuff to complain about with ai these days like stable diffusion image generation and LLMs, but the fact that they are AI is simply true.
I mean it’s entirely an arbitrary distinction. AI, for a very long time before chatGPT, meant something like AGI. we didn’t call classification models ‘intelligent’ because it didn’t have any human-like characteristics. It’s as silly as saying a regression model is AI. They aren’t intelligent things.
I once had ideas about building a machine learning program to assist workflows in Emergency Departments, and its’ training data would be entirely generated by the specific ER it’s deployed in. Because of differences in populations, the data is not always readily transferable between departments.
