41–50 of 68 posts
I work in this space. The breakthrough will most likely come from computational biologists, not an external ML group. Liquid biopsy is close and that's the domain that reeeallly needs ML/AI in additional to strong mechanistic models.
That's okay, though, right? We're not talking about fully automating diagnosis and treatment. We're talking about using a tool to help doctors diagnose and treat more effectively. i.e. it's more like predictive text input than anything. If it makes it faster for you to diagnose, makes harder to diagnose stuff easier, and recommends the right treatment most of the time then it saves the doctor some time and energy. Th…
Earlier quoted context omitted.
Instead of autopilot, think of this as (or should be) more like fly-by-wire systems in every modern fighter jet. The computer reads the pilot's inputs and translates them to the most effective possible control adjustments, making many more changes than a pilot would be able to make even given the controls. Or maybe the tool should be limited to retrospective evaluation of doctors' decisions. Basically an automated pe…
I would argue against this one, simply because of the Airbus incident from some time ago where to avoid pushing feedback into the controls, the plane was designed to average out the inputs from the two pilots. The older, more experienced pilot was attempting to maneuver the plane in such a way to correct their problem (I believe it was a stall) and the younger pilot was panicking and attempting the opposite maneuver,…
The fly-by-wire control system ordinarily prevents stalls, but it had disengaged due to an iced over sensor and was operating without stall protection. The plane stalled at 38,000 feet and fell into the ocean.
They should have had plenty of time to correct the stall, but one pilot was pulling back his control stick (the opposite of what they needed to do), and since the two sticks aren't physically linked the other pilot didn't know he was doing that.
It's one of the topics discussed in the podcast that I linked above.
That's okay, though, right? We're not talking about fully automating diagnosis and treatment. We're talking about using a tool to help doctors diagnose and treat more effectively. i.e. it's more like predictive text input than anything. If it makes it faster for you to diagnose, makes harder to diagnose stuff easier, and recommends the right treatment most of the time then it saves the doctor some time and energy. Th…
Having systems like autopilot in planes can make pilots worse at flying because they don't spend as much time practicing at the controls and monitoring what's happening. Then when something goes wrong, they risk not paying close enough attention to catch it, or not being practiced well enough to correct it. If you get complacent and just assume the computer knows what it's doing (because it usually does) this can and…
Two incidents demonstrate that:
1. https://en.wikipedia.org/wiki/Asiana_Airlines_Flight_214
2. https://en.wikipedia.org/wiki/Air_France_Flight_447
Pilots on both came from the civilian background. The difference between civilian training and combat training is that the latter is more trained to operate in conditions that involve instruments failure, distress, etc.
Earlier quoted context omitted.
I would argue against this one, simply because of the Airbus incident from some time ago where to avoid pushing feedback into the controls, the plane was designed to average out the inputs from the two pilots. The older, more experienced pilot was attempting to maneuver the plane in such a way to correct their problem (I believe it was a stall) and the younger pilot was panicking and attempting the opposite maneuver,…
For reference, I believe this is the crash you're referring to: https://en.wikipedia.org/wiki/Air_France_Flight_447 The fly-by-wire control system ordinarily prevents stalls, but it had disengaged due to an iced over sensor and was operating without stall protection. The plane stalled at 38,000 feet and fell into the ocean. They should have had plenty of time to correct the stall, but one pilot was pulling back his c…
Earlier quoted context omitted.
Should have partnered with Google if you actually wanted something that works. IBM had its heyday, but the brain drain of talent and knowledge has already happened and it likely will never recover.
Is that also true of their quantum computing researchers? It does look like they put out some pretty decent research in that area.
Why not look through the papers each company has released though and decide for yourself? https://ai.google/research/teams/applied-science/quantum-ai/ https://www.ibm.com/blogs/research/category/quantcomp/
That's okay, though, right? We're not talking about fully automating diagnosis and treatment. We're talking about using a tool to help doctors diagnose and treat more effectively. i.e. it's more like predictive text input than anything. If it makes it faster for you to diagnose, makes harder to diagnose stuff easier, and recommends the right treatment most of the time then it saves the doctor some time and energy. Th…
Having systems like autopilot in planes can make pilots worse at flying because they don't spend as much time practicing at the controls and monitoring what's happening. Then when something goes wrong, they risk not paying close enough attention to catch it, or not being practiced well enough to correct it. If you get complacent and just assume the computer knows what it's doing (because it usually does) this can and…
That's okay, though, right? We're not talking about fully automating diagnosis and treatment. We're talking about using a tool to help doctors diagnose and treat more effectively. i.e. it's more like predictive text input than anything. If it makes it faster for you to diagnose, makes harder to diagnose stuff easier, and recommends the right treatment most of the time then it saves the doctor some time and energy. Th…
We're talking about using a tool to help doctors diagnose and treat more effectively. A very expensive tool when healthcare systems are strapped for cash. Super unethical of IBM to try and extract profits here.
Do you realize they would have never developed Watson if there weren't profits involved?
I work in this space. The breakthrough will most likely come from computational biologists, not an external ML group. Liquid biopsy is close and that's the domain that reeeallly needs ML/AI in additional to strong mechanistic models.
What’s liquid biopsy?
a biopsy from your peripheral plasma, opposed to solid tumor. A big issue in cancer medicine is it's super fucking hard to get any kind of noninvasive measurement. Typically it's done with surgery or with CAT scans, which have extremely low precision.
Research in the last few years has been pointing to the idea that we can detect tumor derived DNA fragments in plasma. The challenge being, healthy dna makes up 99.9% of it, this means that currently the methods only work when the tumor burden (metastatic for instance) is high. Not ideal for early detection or treatment monitoring. But if the computational tools improve (rn none assume such a low mixture), you could see sensitivity and precision increase to the point that it's useful for predicting therapeutic outcomes and for early detection.