So much FUD on this thread. If a doctor can identify something fishy on a x-ray OF COURSE an appropriate machine learning algorithm can do it as well. It's just a question of gathering the right dataset and experimenting with different architectures.
Machine learning is booming in medicine, but also facing a credibility crisis
81–90 of 100 posts
Re: Machine learning is booming in medicine, but also facing a credibility crisis
#82Earlier quoted context omitted.
Why not build something on your spare time and try to create your own job then?
Founding a startup is not an option available to everyone. It takes money and other resources. And for some of the same reasons that I am unemployed despite valuable skills, it is virtually impossible for me to get any funding.
I completely disagree with you, bootstrapping your own internet company doesn't cost a lot. Except effort and time.
You can fund it yourself with basically any income. Of course you will never get anywhere with an attitude like the one you currently have.
It's not the skill or resources that is the problem, it's the mindset.
Re: Machine learning is booming in medicine, but also facing a credibility crisis
#83Unless the AI can talk tot the patient to get some context, it's going to be taking decisions with only very partial information, no matter how good it is. Still, I'm thinking that as it improves, it's going to show that doctors are not that good at their job on average, and that's going to be fun to watch.
> Still, I'm thinking that as it improves, it's going to show that doctors are not that good at their job on average, and that's going to be fun to watch.
Medical AI is trained on labels generated by doctors. Can you explain how it will exceed the performance of doctors on average? Are you assuming that the labels will be generated by the "top x%" of doctors? If so, how will you identify those individuals? Or is there some other mechanism you're expecting to improve the performance?
Re: Machine learning is booming in medicine, but also facing a credibility crisis
#84Some radiologists think that AI will be really good for filtering out normal images, so that they only have to review anomalies. But I don't think that a model that detects diseases will be too successful, even if they manage to make it really work. For one, it's actually difficult to interpret and find signs in radiologic images. Obvious signs are obvious, but there are others that could be image artifacts, or just…
>Some radiologists think that AI will be really good for filtering out normal images, so that they only have to review anomalies. But I don't think that a model that detects diseases will be too successful, even if they manage to make it really work. Radiologists say this until they get malpractice lawsuits. Seriously, I once injured my wrist and the first radiologist said it was just a sprain, but no surprise the ho…
Sure but why not take the best of both worlds? Make a ai analyze your wrist fracture and also a radiologist analyze it. If the results don’t agree then you need to re-analyze.
That would even drive down the possibility of malpractice.
Re: Machine learning is booming in medicine, but also facing a credibility crisis
#85Earlier quoted context omitted.
I was thinking more like ultrasound. If some crude scanner was cheap enough for every GP's office to have, and an AI could decipher the noisy signal which is perhaps too messy for a human to read, it could be used routinely like blood pressure measurement and stethoscopes are. If it's a regular screening test rather than a response to the patient's complaint, then false negatives wouldn't be as much of a problem beca…
I had an abdominal ultrasound recently - the actual process of placing the probe and annotating the images seems like a pretty specific technical skill. I don't think any old person (or even a doctor) off the street can just rub the wand on you and find your kidneys for instance.
That's the idea of using AI. So the operator doesn't have to be skilled at identifying things.
Re: Machine learning is booming in medicine, but also facing a credibility crisis
#86Earlier quoted context omitted.
I was thinking more like ultrasound. If some crude scanner was cheap enough for every GP's office to have, and an AI could decipher the noisy signal which is perhaps too messy for a human to read, it could be used routinely like blood pressure measurement and stethoscopes are. If it's a regular screening test rather than a response to the patient's complaint, then false negatives wouldn't be as much of a problem beca…
Ultrasound scanners are fairly cheap. But operating them is not easy, you still need training to use them and know what you're looking at. > it's better than nothing. Not necessarily, that's the issue with screening asymptomatic people. You have to balance the consequences and rates of false positives with the benefits of true positives. If ultrasound screening mostly catches indolent diseases, or those where catchin…
I know that can be an issue but like you say, there's a balance and I don't think we know where that balance is for the non-existent AI technology with unknown error rates.
Newborn babies undergo a whole lot of simple and inaccurate screenings. I guess those are cases where the harm due to inappropriate treatments is lower than that due to leaving diseases undetected.
Either way, I'd rather the technology exist and then people work out how best to use it, rather than the decision being forced on us by it not existing.
Re: Machine learning is booming in medicine, but also facing a credibility crisis
#87Some radiologists think that AI will be really good for filtering out normal images, so that they only have to review anomalies. But I don't think that a model that detects diseases will be too successful, even if they manage to make it really work. For one, it's actually difficult to interpret and find signs in radiologic images. Obvious signs are obvious, but there are others that could be image artifacts, or just…
Your argument would be better if you stated that most diseases are diagnosed at an advanced stage when it's obvious. The rest are incidental and then we sometimes occasionally we get lucky. We don't routinely CT scan people because it's harmful to do so.
Re: Machine learning is booming in medicine, but also facing a credibility crisis
#88Earlier quoted context omitted.
I had an abdominal ultrasound recently - the actual process of placing the probe and annotating the images seems like a pretty specific technical skill. I don't think any old person (or even a doctor) off the street can just rub the wand on you and find your kidneys for instance.
That's the idea of using AI. So the operator doesn't have to be skilled at identifying things.
I have had an abnormal ultrasound and then a CT negative. If AI can cut down the CTs it's a win.
Re: Machine learning is booming in medicine, but also facing a credibility crisis
#89Earlier quoted context omitted.
>Some radiologists think that AI will be really good for filtering out normal images, so that they only have to review anomalies. But I don't think that a model that detects diseases will be too successful, even if they manage to make it really work. Radiologists say this until they get malpractice lawsuits. Seriously, I once injured my wrist and the first radiologist said it was just a sprain, but no surprise the ho…
Sure but why not take the best of both worlds? Make a ai analyze your wrist fracture and also a radiologist analyze it. If the results don’t agree then you need to re-analyze. That would even drive down the possibility of malpractice.
A radiologist would have insurance in place for malpractice that indemnifies her/him. So your suggestion that a radiologist would be motivated to use AI to reduce this risk does not seem applicable to me. The idea to run AI alongside the human tool seems to be the current default suggestion these days, now that we have collectively realised that AI cannot do anything serious on its own. Pair it up with a human and the two can work together, with some handholding. But it is a hard sell, the software is now just duplicating a capability, and all of the issues that raises of potentially having two answers to one question. As a radiologist business, you would have to dedicate manpower to investigating when the AI has a different answer. Honestly, if I had a radiology practice, considering the points above, my answer would be no.
Re: Machine learning is booming in medicine, but also facing a credibility crisis
#90I would really like to get a job in medical ML, but without a related degree it seems impossible. I'm "only" a Veterinarian and I don't even get interviews...
Reading some of your replies, you are good at coming up with reasons you cannot be successful. A friendly suggestion: this attitude may be holding you back more than you realized before now. What to do instead, is repeatedly ask yourself: "how can I do this?" Apply this to many specific areas: - How can I change my CV so it comes across differently? - How can I begin a small startup without money or other resources?…
Those are all very obvious questions that I have been asking myself for years, without finding useful answers.
The objective reality is that I did not succeed. Somehow people think accepting that means I have a negative attitude. I haven't given up on ever working again, but I'm not delusional enough to think I haven't been unemployed for a long time.