An artificial intelligence model from the Mayo Clinic detected abnormalities on scans up to three years before patients were diagnosed. It's being evaluated in a clinical trial.
False positives are at least as dangerous as false negatives and AI solutions like this have massive problems with over diagnosing.
Absolutely 100% wrong.
In pancreatic ductal adenocarcinoma, a false positive means a follow-up scan. A false negative means death, the 5-year survival is near zero once it’s caught late, but exceeds 80% when caught early.
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Saw your edit. I’m not a “home-bound tech worker” and I think you’re projecting. What’re your medical qualifications?
Absolutely 100% wrong.
In pancreatic ductal adenocarcinoma, a false positive means a follow-up scan. A false negative means death, the 5-year survival is near zero once it’s caught late, but exceeds 80% when caught early.
In the study, the radiologists’ lower false positive rate is achieved by missing 78% of cancers. That’s not a safer trade-off, it’s just a different way to fail. “Overdiagnosis” also requires a disease that might not have harmed the patient, PDA doesn’t have a harmless form. Every missed case is a lost life while every false positive is an extra doctor’s appointment.
This system detects twice as many cancers and was flagging them, on average, 675 days (nearly 2 years!) before clinical detection.
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They selected the pathology that’s the topic of the post to support their on-topic argument. Be better, indeed.
Really wish people could be better collaborators instead of just being jerks. Kills any value in the conversation.
You’re rude, arrogant, and wildly incorrect from a medical standpoint. Please delete your message and don’t make comments like this in the future.
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