5 ms·

That argument is exactly the one made by my former company, Rad AI. Rather than focusing on trying to "solve" radiology they're focused on augmenting radiologis

by tedivm 5y ago

That argument is exactly the one made by my former company, Rad AI. Rather than focusing on trying to "solve" radiology they're focused on augmenting radiologists. Their main goal is to reduce the amount of time a radiologist spends on each report while increasing accuracy and reducing errors. The point I'm making is that focusing on mammograms is not the way to do that. It's already a very optimized specialty. If AI researchers worked more closely with practicing radiologists (not academic ones) I imagine there's all sorts of areas where existing technology today can improve things.

antasvara 5y ago
I think my point is that mammograms are a (relatively) easy to solve problem using today's technology. Why wouldn't it be worthwhile to solve that problem such that it has very limited human involvement? It's the reason professional baseball is experimenting with electronic strike detection, despite the fact that umpires are very accurate (~94%) calling pitches. I get that there are useful applications of AI that could augment a radiologist. I'm simply pointing out that if one could completely remove a radiologist from the equation, that could be a super helpful tool. I suppose my view is that removing/limiting the human element in routine inspections is a very worthwhile goal. There's also the side benefit of increasing trust for these technologies. I think a lot of people are rightfully scared of AI technologies; showing that they can be as effective as a radiologist for routine screenings would be very beneficial.
cameronh90 5y ago
"If AI researchers worked more closely with practicing radiologists (not academic ones) I imagine there's all sorts of areas where existing technology today can improve things." That's almost certainly true, and surely there must be people in the medical industry already working on this. In hospitals, there are internal organisations that vaguely attempt to link up technology workers with practicing doctors to improve medicine using technology. One of my most competent former developer colleagues retrained as a doctor and worked in medical digitisation, as well as being a practicing doctor. However: * Often coming at a problem from another angle and ignoring existing professionals can be useful too. Existing workers are very often stuck in their ways and unwilling to accept the way they look at a problem may not be the best. I have heard from many in medicine, that doctors are extremely distrustful and hesitant towards technology, as well as fiercely protective of their jobs. * The medical industry is internally highly dysfunctional and trying to work with practicing doctors can be extremely politically difficult. The hospital bureaucracy often actively tries to prevent practicing doctors from working directly with technologists, preferring instead to silo them and direct all communication via senior management - who are often neither technology nor medical experts. Consequently it seems more likely that major changes will come from outside. * AI has occasionally (rarely?) shown great success in solving problems without needing domain experts. See AlphaGo.
- xvilka 5y ago
  > AI has occasionally (rarely?) shown great success in solving problems without needing domain experts. See AlphaGo. Games are always orders of magnitudes easier then analyzing reality. They are highly constrained to the narrow domain and space of possibilities. Reality doesn't. There is work on understanding physical laws by the AI but it's very long path and they are much less successful than their artificial reality colleagues.
  - sdenton4 5y ago
    In just a few decades we've gone from 'chess is ai complete' to 'go is ai complete?' to 'games are too easy to be meaningful.' In game domains we have the ability to generate infinite meaningful training data and have easily measured outcomes. Waymo is generating near infinite data for driving, and doing quite well with it. In medicine, we have piddly ass datasets because of privacy concerns. 'Reality is hard' had nothing to do with it.
    - danielmarkbruce 5y ago
      Reality is hard is still a thing. Google has the ability to spends billions (or 10's) on something like Waymo and they still have to spend billions (or 10's) more to properly commercialize it. This isn't going to be a commonly done thing.
    - deleted 5y ago
      [deleted]
- tedivm 5y ago
  > The medical industry is internally highly dysfunctional and trying to work with practicing doctors can be extremely politically difficult. The hospital bureaucracy often actively tries to prevent practicing doctors from working directly with technologists, preferring instead to silo them and direct all communication via senior management - who are often neither technology nor medical experts. Consequently it seems more likely that major changes will come from outside. This is one of the areas where working with radiologists actually makes things easier. Radiology groups are normally independent practices that contract with multiple hospitals- they link in with hospital systems but mostly run their own thing. They also tend to have really solid IT departments and enough funding to make things work. Working with hospitals is a nightmare though, as you say.

by tedivm 5y ago

antasvara 5y ago

I think my point is that mammograms are a (relatively) easy to solve problem using today's technology. Why wouldn't it be worthwhile to solve that problem such that it has very limited human involvement? It's the reason professional baseball is experimenting with electronic strike detection, despite the fact that umpires are very accurate (~94%) calling pitches. I get that there are useful applications of AI that could augment a radiologist. I'm simply pointing out that if one could completely remove a radiologist from the equation, that could be a super helpful tool. I suppose my view is that removing/limiting the human element in routine inspections is a very worthwhile goal. There's also the side benefit of increasing trust for these technologies. I think a lot of people are rightfully scared of AI technologies; showing that they can be as effective as a radiologist for routine screenings would be very beneficial.

cameronh90 5y ago

"If AI researchers worked more closely with practicing radiologists (not academic ones) I imagine there's all sorts of areas where existing technology today can improve things." That's almost certainly true, and surely there must be people in the medical industry already working on this. In hospitals, there are internal organisations that vaguely attempt to link up technology workers with practicing doctors to improve medicine using technology. One of my most competent former developer colleagues retrained as a doctor and worked in medical digitisation, as well as being a practicing doctor. However: * Often coming at a problem from another angle and ignoring existing professionals can be useful too. Existing workers are very often stuck in their ways and unwilling to accept the way they look at a problem may not be the best. I have heard from many in medicine, that doctors are extremely distrustful and hesitant towards technology, as well as fiercely protective of their jobs. * The medical industry is internally highly dysfunctional and trying to work with practicing doctors can be extremely politically difficult. The hospital bureaucracy often actively tries to prevent practicing doctors from working directly with technologists, preferring instead to silo them and direct all communication via senior management - who are often neither technology nor medical experts. Consequently it seems more likely that major changes will come from outside. * AI has occasionally (rarely?) shown great success in solving problems without needing domain experts. See AlphaGo.

xvilka 5y ago
> AI has occasionally (rarely?) shown great success in solving problems without needing domain experts. See AlphaGo. Games are always orders of magnitudes easier then analyzing reality. They are highly constrained to the narrow domain and space of possibilities. Reality doesn't. There is work on understanding physical laws by the AI but it's very long path and they are much less successful than their artificial reality colleagues.
- sdenton4 5y ago
  In just a few decades we've gone from 'chess is ai complete' to 'go is ai complete?' to 'games are too easy to be meaningful.' In game domains we have the ability to generate infinite meaningful training data and have easily measured outcomes. Waymo is generating near infinite data for driving, and doing quite well with it. In medicine, we have piddly ass datasets because of privacy concerns. 'Reality is hard' had nothing to do with it.
  - danielmarkbruce 5y ago
    Reality is hard is still a thing. Google has the ability to spends billions (or 10's) on something like Waymo and they still have to spend billions (or 10's) more to properly commercialize it. This isn't going to be a commonly done thing.
  - deleted 5y ago
    [deleted]
tedivm 5y ago
> The medical industry is internally highly dysfunctional and trying to work with practicing doctors can be extremely politically difficult. The hospital bureaucracy often actively tries to prevent practicing doctors from working directly with technologists, preferring instead to silo them and direct all communication via senior management - who are often neither technology nor medical experts. Consequently it seems more likely that major changes will come from outside. This is one of the areas where working with radiologists actually makes things easier. Radiology groups are normally independent practices that contract with multiple hospitals- they link in with hospital systems but mostly run their own thing. They also tend to have really solid IT departments and enough funding to make things work. Working with hospitals is a nightmare though, as you say.