This reminds me of Machine Learning techniques being used at the Policlinico of Bari in collaboration with the Politecnico of Bari, detective cancer, more than 10 years ago
AI used for skin cancer checks at London hospital
71–80 of 91 posts
Re: AI used for skin cancer checks at London hospital
#72Earlier quoted context omitted.
Not really. It allows you to order your cases from most-likely to least-likely, and get human eyeballs on the most-likely cases first.
This is how most ML in healthcare is used. It's a fantasy to think we can give all patients equal attention, so it often makes sense to prioritize those most at risk. Of course no model is perfect, but ML can be very beneficial when used in the right context (i.e. not like United Healthcare).
Yup. The word I should have used is "triage".
Re: AI used for skin cancer checks at London hospital
#73Earlier quoted context omitted.
It's quite easy to correctly classify 100% of benign cases as benign.
If it's so easy, then why do people die from having lesions misdiagnosed as benign? Even if the success rate of the human eye was in the 99.5%+ range, why not have an extra sanity check from an AI model?
Because this non-AI function 'correctly diagnoses 100% benign cases as benign':
def is_benign(mole: Image) -> bool:
return True
Re: AI used for skin cancer checks at London hospital
#74This would be such a beautiful use of AI
No, it's a horrible use, relying on something entirely unreliable to make medical diagnoses. All the AI safety people who pretend to worry about killer robots or whatever should actually be up in arms about these kind of uses, but you can see where actual priorities lie.
The best use of AI in medicine would be to automate away administrative bloat to let people get proper medical care.
Re: AI used for skin cancer checks at London hospital
#75This would be such a beautiful use of AI
No, it's a horrible use, relying on something entirely unreliable to make medical diagnoses. All the AI safety people who pretend to worry about killer robots or whatever should actually be up in arms about these kind of uses, but you can see where actual priorities lie. The best use of AI in medicine would be to automate away administrative bloat to let people get proper medical care.
What if it was really reliable? Would you still be against it?
Re: AI used for skin cancer checks at London hospital
#76Anecdotally, when I had a potential skin cancer checked at a London hospital they were completely ill-prepared. When I came back to Australia, it was checked and immediately removed as an obvious melanoma. Perhaps the idea of Comparative Advantage also applies to healthcare between countries with natural variances to types of disease?
Sadly, a friend of mine died from this type of problem. He traveled from Ghana to Jordan and fell ill in Jordan, the Jordanian doctors didn't diagnose it as malaria in time to save him because Jordan doesn't have malaria. I'm sure it would have been obvious to a Ghanaian doctor.
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Re: AI used for skin cancer checks at London hospital
#77Earlier quoted context omitted.
When I first heard the clinical idiom "When you hear hoof-beats, think horses not zebras" I thought it was a precautionary saying about the bias toward assuming the familiar. But it's meant to be instructive!
No, that’s backwards. It means what it says. When you see a symptom first look for the common things it could be, not the one in a million chance.
We have a formal description of this, it's called bayes theorem.
The Jordanian doctors just had poor priors.
Re: AI used for skin cancer checks at London hospital
#78Earlier quoted context omitted.
No, it's a horrible use, relying on something entirely unreliable to make medical diagnoses. All the AI safety people who pretend to worry about killer robots or whatever should actually be up in arms about these kind of uses, but you can see where actual priorities lie. The best use of AI in medicine would be to automate away administrative bloat to let people get proper medical care.
What if it was really reliable? Would you still be against it?
The question doesn't make sense imo because it, meaning neural network or other ML computer vision classification, doesn't have a mechanism to be trustworthy. It's just looking for shortcuts with predictive power, it's not reasoning, doesn't have a world model, it's just an equation that mostly works, etc, all the stuff we know about ML. It's not just about validation set performance, you could change the lighting or some camera feature or something, have some unusual mole shape, and suddenly get completely different performance. It can't be "trusted" the way a person can, even if they are less accurate.
These limitations are often acceptable but I think as long as it works how it does, denying someone a person looking at them in favor of a statistical stereotype should be the last thing we do.
I can see if this was in a third world country and the alternative was nothing, but in the developed world the alternative is less profit or fewer administrators. We should strongly reject outsourcing the actual medical care part of healthcare to AI as an efficiency measure.
Re: AI used for skin cancer checks at London hospital
#79Earlier quoted context omitted.
No, that’s backwards. It means what it says. When you see a symptom first look for the common things it could be, not the one in a million chance.
We have a formal description of this, it's called bayes theorem. The Jordanian doctors just had poor priors.
In this particular case, "when you see stripes with hoofbeats, think zebra, not horse with a paintjob"
Re: AI used for skin cancer checks at London hospital
#80Earlier quoted context omitted.
What if it was really reliable? Would you still be against it?
The question doesn't make sense imo because it, meaning neural network or other ML computer vision classification, doesn't have a mechanism to be trustworthy. It's just looking for shortcuts with predictive power, it's not reasoning, doesn't have a world model, it's just an equation that mostly works, etc, all the stuff we know about ML. It's not just about validation set performance, you could change the lighting or…
I understood that you don't believe it can be made reliable. But my question was: what if it were?
Let me put it differently. Suppose I don't tell you it's ML. It's a machine that you don't know how it works, but I let you do all the tests you want, and turns out they're great. Would you then still be against it?