AI can find cancer pathologists miss
AI can find cancer pathologists miss
www.uu.se
AI can find cancer pathologists miss - Uppsala University
cross-posted from: https://programming.dev/post/36236133
Comments
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Who is downvoting progress in Cancer identification?
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Lemmings with knee-jerk reactions to anything AI related
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Ohhh, this 100%
I just posted a plaque imaging study using AI analysis showing people eating the carnivore diet reversing plaque buildup by doing over a year of a strict ketogenic diet.
People I could have offended
- AI
- diet zealots
- anti-keto reactionaries
- CICO advocates
But instead I used a name without any of the trigger words and they missed it
We could rewrite this headline as:
Advanced identification techniques let doctors diagnose cancer earlier saving lives!
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I was about to post a comment: Finally a use for AI that feels justified to spend energy on.
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There was also a study going around claiming that llms caused cancer screenings by humans to decrease in accuracy. I'm not a scientist but I'm pretty sure the sample size was super small and localized in one hospital?
Anyway maybe they're remembering that in addition to the automatic AI hating down votes.
Not that I'm a fan of AI being shoved everywhere but this isn't that
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Why would you use a large language model to examine a biopsy?
These should be specialized models trained off structured data sets, not the unbridled chaos of an LLM. They're both called "AI", but they're wildly different technologies.
It's like criticizing a doctor for relying on an air conditioner to keep samples cool when I fact they used a freezer, simply because the mechanism of refrigeration is similar.
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But the title had "AI" in it.
Also to answer your question: https://lemvotes.org/post/programming.dev/post/36238264
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After reading the actual published science paper referenced in the article, I would downvote the article because the title is clickbaity and does not reflect the conclusions of the paper. The title suggests that AI could replace pathologists, or that pathologists are inept. This is not the case. Better title would be "Pathologists use AI to determine if biopsied tissue samples contain markers for cancerous tissue that is outside the biopsied region."
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RFK
Cancer causes autism
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From the article: " All 232 men in the study were assessed as healthy when their biopsies were examined by pathologists. After less than two-and-a-half years, half of the men in the study had developed aggressive prostate cancer...."
HALF? I'd suggest staying away from that study ... either they don't know what they're doing, or some AI made up that article...
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From the peer-reviewed paper: "This study examined if artificial intelligence (AI) could detect these morphological clues in benign biopsies from men with elevated prostate-specific antigen (PSA) levels to predict subsequent diagnosis of clinically significant PCa within 30 months".. so yes, these were men who all had high cancer risk.
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And the risk of prostate cancer from age 60 on is quite high and increases with age, even if you're not in a high risk group (other than age).
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OK, thanks for that clarification. I was thrown off by 'assessed as healthy...'
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Maybe they specifically picked men with increased risk?
Half sounds pretty nuts otherwise.
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Yes they did. It says so in the article.
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ba dum tss
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Well, it's likely that AI is creating these articles. We're just like in 1984...
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Good, use it for that. It fucking sucks at art.
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Different kind of ai. This is the very useful analytical kind.
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Yes, this is one of the kinds of AI I love
The plagiarism machines are the kind most of us can't stand
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Yep. My thesis is that a larger share of AI investment and energy should be directed toward more promising areas.
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What's the false positive rate? You can dial up the sensitivity of any test if you don't mind 10,000 people having unnecessary cancer surgery for every real case that's detected.
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this is bullshit.
the study was performed by Navinci Diagnostics, which has a vested interest in the use of technological diagnostic tools like AI.
the only way to truly identify cancer is through physical examination and tests. instead of wasting resources on AI we should improve early detection through improved efficiency of tests, allowing patients to regularly test more often and cheaper.
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Won't this sort of technology help people get regular tests more often?
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it won't because it's an illusion of a test with unverifiable results.
Imagine this, you want to know if you have cancer. you can get results from a biopsy, blood tests, and an MRI. all results are validated by specialist review. it will take 3 months to collect and validate the results. OR, you can run all your tests above and have results in 24 hours but they aren't validated by a specialist.
so the question is, why does it take 3 months and how can we make it shorter without decreasing quality, validity, or consistency?
AI is not the answer.
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I thought the article was telling an unmarried woman that AI can find the cancer pathologists she's been looking for. Not sure why they would be hiding.
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Don’t quit your day job.
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I thought AI had trouble spelling Pennsylvania
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But I wouldn't count on miracles, these freaks at the top will use this AI for their own vile purposes.
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This is pattern recognition actual AI. Not LLM plagiarism code
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This is what machine learning is supposed to be. Specialized models that solve a specific problem. Refreshing to read about some real AI research
I feel like in an ideal world, people can be using AI to help the quality of their work. Rather than being replaced by AI itself.
We live in a world where the strong take the last food from the weak in order to live even more luxuriously, because luxury, so to speak, is created through stolen or simply slave labor.
In short, the rich are rich only because they exploit the poor or simply slaves, otherwise they would be beggars or middle class.
Yeah, this is a typical place for AI to actually shine and we hear almost nothing about it because making fake porn videos of your daughter in law is somehow more important
Yeah, there are some useful applications for ML. Less so for LLMs.