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re: Which medical field is most resistance to automation and AI?
Posted on 1/31/19 at 3:25 pm to Bjorn Cyborg
Posted on 1/31/19 at 3:25 pm to Bjorn Cyborg
The AI better be the Dr too, because good luck getting the oncologist, or whoever, to understand how the AI describes the case.
Posted on 1/31/19 at 3:29 pm to Bjorn Cyborg
quote:
OB/GYN
Males are vanishing in this field.
Posted on 1/31/19 at 3:30 pm to Bjorn Cyborg
I deal in cancer diagnostics and we already have algorithms that score patients. Pathologists want it as an aide, but it would technically do their job for them in most cases.
Posted on 1/31/19 at 3:30 pm to Gaston
quote:For a human, maybe.
Wow, that’s incredibly wrong. It’s damn near impossible to give a yes or no answer in that field.
quote:All the more reason many people are determined to automate it.
One of my friends does it, and there’s a reason he makes an incredible amount of money.
quote:It's difficult mostly because you have to spend a lot of time looking at every little detail, and know what you're looking at. These are things that computers are getting very, very good at doing.
It’s incredibly difficult.
I hope your friend's school loans are paid off, because he might be out of a job in the next few years.
Posted on 1/31/19 at 3:33 pm to Gaston
quote:This is the easiest part to automate.
The AI better be the Dr too, because good luck getting the oncologist, or whoever, to understand how the AI describes the case.
Posted on 1/31/19 at 3:36 pm to Korkstand
He started at $700k/yr a long damn time ago. He says that so many damn PAs order shite they don’t need, and the DRs want yes/no answers to shite there is no yes/no for. I think he reads ~150 cases a shift...I’m sure he’d be fine with a pay cut in exchange for the 100 easy ones being read by a computer.
Posted on 1/31/19 at 3:38 pm to Korkstand
quote:
the easiest part
My friend graduated, Davidson, with an English Lit degree and describe things incredibly well...he says the Drs don’t ‘get’ his descriptions...how’s this going to be easy?
Posted on 1/31/19 at 3:39 pm to Gaston
quote:
The AI better be the Dr too, because good luck getting the oncologist, or whoever, to understand how the AI describes the case.
The tests that we do point to what treatment would be effective. The actual information going to the oncologist would be very simple.
Posted on 1/31/19 at 3:44 pm to Gaston
quote:
My friend graduated, Davidson, with an English Lit degree and describe things incredibly well...he says the Drs don’t ‘get’ his descriptions...how’s this going to be easy?
Wish I could go into more detail, but you have a pathologist looking at tissue counting cells and looking at the reactivity to the cells with reagents. In the past it has always been "positive/negative". Advanced diagnostics uses antibodies which expresses in specific types of cancer. The report that the Path puts together is this simple information. Same thing my software is doing.
Posted on 1/31/19 at 3:46 pm to flyAU
Not arguing that. Just saying that to my radiologist friend things are getting more difficult for them not easier.
Posted on 1/31/19 at 3:48 pm to NIH
quote:
I always get a kick out of a board full of engineers, salesmen, and "consultants" cheering on AI
Engineering will be the dead last thing that AI will be able to replicate. The creativity needed for proper engineering will be incredibly difficult to replicate.
AI is good and will get better at reading MRI data. But it will be incredibly difficult for AI to build a better MRI machine/alternative. We will all be dead before that comes around. Maybe our children or grandchildren will see that day.
Posted on 1/31/19 at 3:49 pm to Gaston
quote:
Not arguing that. Just saying that to my radiologist friend things are getting more difficult for them not easier.
Which actually bodes well for an AI crunching the information and reporting it to a doctor in easily digestible information. In the end, an X-ray is 1's and 0's in their Pacs system. Computer aided (eventual replacement) will happen if we want more advanced care.
Posted on 1/31/19 at 3:54 pm to Gaston
quote:I don't think you quite grasp how dramatic the difference is between a person reading 150 images per shift, and a computer reading 150 images per second. One way costs thousands of dollars and 12 hours, and the other costs a fraction of a penny and one second. And the cheaper way is more accurate, to boot.
I think he reads ~150 cases a shift...I’m sure he’d be fine with a pay cut in exchange for the 100 easy ones being read by a computer.
A computer can look at an image, find any issues that it has been "trained" to find, and then store a perfect copy of the entire image in its memory for later. There might be something innocuous in that image that showed up on other images from other patients, and those patients later on developed a problem. No human can do the type of analysis that a computer can. And once you've trained one, you've trained them all. You don't have to send each and every computer through expensive medical school.
Posted on 1/31/19 at 3:56 pm to Gaston
quote:I'm not sure you understand the point of computers.
My friend graduated, Davidson, with an English Lit degree and describe things incredibly well...he says the Drs don’t ‘get’ his descriptions...how’s this going to be easy?
The same computer can describe the same image to a thousand different doctors in a manner that each doctor can best understand.
Posted on 1/31/19 at 3:58 pm to Bjorn Cyborg
Did you even read your links?
AI can be helpful, but lacks human judgement for critical decision making.
AI can be helpful, but lacks human judgement for critical decision making.
quote:
AI offers a major opportunity to enhance and augment radiology reading, not to replace radiologists.
Posted on 1/31/19 at 3:58 pm to Gaston
quote:That's because he's an imperfect person dealing with imperfect people.
Just saying that to my radiologist friend things are getting more difficult for them not easier.
Posted on 1/31/19 at 4:00 pm to Korkstand
quote:
There might be something innocuous in that image that showed up on other images from other patients, and those patients later on developed a problem.
You know what you are talking about.
End goal is to find the patterns in patients amid the myriad of tests performed. This has started out with algorithm's and will build to specific AI's that correlate data from all patients to find specific traits/factors which can point to effective treatment as well as the holy grail: identifying who is going to have these problems and attack them before they happen. Heart medicine before heart problems etc. The goal is negate the illness as much as possible.
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