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I'm a radiology resident with a master's in computer science. It's great that healthcare organizations are finally releasing larger datasets. There's much progr

I'm a radiology resident with a master's in computer science. It's great that healthcare organizations are finally releasing larger datasets. There's much progress to be made in medical ML/AI. However, my attitude towards radiology AI startups has changed quite a bit since starting residency. There really isn't a sustainable business model that involves selling standalone AI products, or even software suites. I think AI is a feature for the scanner, the PACS or for existing dictation software. That is, I think PowerScribe or GE would help a lot of radiologists by integrating AI features into their existing tech stacks. I also think the only feasible exit strategy for radiology AI/ML startups is to get bought out for their tech talent and algorithms. I don't know of any hospitals/clinics/imaging centers that are buying AI products directly from startups. There's a ton of hype, but I'm not aware of a single positive-cash-flow radiology AI company.

dontreact 8y ago
I think you’re taking this viewpoint quite prematurely. It’s been about 3 years since we found architectures that surpass human level performance. The process in medicine is slow. FDA, billing codes etc. Give it 3 more years before drawing strong conclusions like this.
- hef19898 8y ago
  It might be a strong conclusion, but a reasonable and qualified one. The technical side of ML/AI does not change the main point, sales, a single. Because even in perfect scenario with a perfect AI/ML product to sell you still need a channel to customers. In this case doctors and hospitals. And from that perspective, considering the trend to full-service solutions for expensive equipment, the manufacturers of scanners are in a much better position to serve the needs of their customers. Good news for ML in general, not so good for all the start-ups out there. But then I have the same doubt regarding the majority of logistics, supply chain and mobility start-ups right now.
  - dontreact 8y ago
    I disagree that the level of performance will not impact the sales picture. The technical side matters a lot for sales. If an AI product is associated with a billing code, that will hugely change the sales dynamic. However this is a high bar to clear in terms of performance. If the algorithms are worse than human level performance then I agree with the assessment. If they are above human level performance, I think the sales picture changes a lot. However this process will happen slowly since it will take time for regulatory and medical community to trust that a particular system truly and robustly outperforms humans.
    - hef19898 8y ago
      This are ver valid points, and I agree with that. You added tue nuance my post was missing.
sna1l 8y ago
It seems like reducing the cost/making MRIs more comfortable would be much more useful. Presumably if the machines didn't cost 3-5 million, with huge energy requirements, etc, you could get scanned a lot more often which probably be better than just using AI/ML? If you were able to scan cancer patients cheaply and quickly for a much lower cost and faster, I'd assume that would have a significant impact.
- FireBeyond 8y ago
  MRIs are typically (from my perspective working in the health insurance industry) profit centers for those who own them. Which leads to perverse incentives, like MRI manufacturers assisting physicians with setting up imaging consortiums, promising recoupment and profits within 18 months. Perhaps unsurprisingly, such doctors order imaging notably more often than others. Low field MRI machines are around $1M. $3M gets you a brand new, state of the art 3 tesla machine.
  - mtgx 8y ago
    Sounds like an obvious "disruption strategy" for a startup here. Why hasn't anyone tried that yet?
    - frozenport 8y ago
      Lol what? Guy just told you the buisness model is making doctors prescribe more treatment than necessary. What are you going to disturpt? Doctors?
    - Aeolos 8y ago
      Patents and huge up-front expenses to create, certify, market and distribute such a device.
    - jayess 8y ago
      Many states limit supply of MRI machines through a "certificate of need" program where you have to convince a regulatory body that you should be allowed to own one.
napban 8y ago
I'm just starting out in a medical career, but keen to pursue a career in Radiology. I'm curious about your background with a computer science degree. Have you found opportunities to make use of your interests in relation to Radiology? My knowledge with computing is just limited to messing around with Linux, but I'm keen to learn more (for fun as well as career development). Are there any pathways you would recommend as high-yield for combining with a career in Radiology? My primary motivation is just enjoying tech, but it would be nice to develop my skills in a direction that allows me to incorporate an element of computing into my future work (whether that be side projects, academic research, or just making me more productive).
npunt 8y ago
This makes some sense both on tech and sales sides. Tech-wise, my guess is the benefits of AI/ML are best exploited at scan time with a scanner integration, rather than after the fact. Specifically, if the algorithm picks up something it can immediately dive in for a closer look while the patient is still there, shortening the turnaround time by weeks. There's also the opportunity to co-develop / tune AI/ML to specific types of scanners. Sales-wise, selling scanners is already a thing, and you don't have to create a new sales channel or figure out how to get buy-in. If a scanner works faster or better than others, hospitals already have a way to understand that through their procurement processes. And you may gain a higher margin by bundling AI/ML reading with hardware. Is this roughly what you see?
thomasfedb 8y ago
Decent datasets are very hard to come by, and the political gymnastics required to create and release them is horrible. I'm keen to create a dataset of paediatric physiological data during anaesthesia to help with event detection/preemption but my professor thinks getting permission to do so is all but impossible.
- YayamiOmate 8y ago
  It's kinda funny to see how relatively easy is to strip people of their general privacy rights for invigilation but how much pushback is there for medical data and medical purposes. Of course everything can be misused, though I would think that improved healthcare is a much better sellingpoint than being physically hurt by some terrorist actor.
- najarvg 8y ago
  I empathize. Pediatric consenting presents challenges more accentuated from what we see in adult patients. Generally we have seen (US academic med centers and hem-onc context) that shifting the focus from baseline expectation of privacy to responsible privacy driven research under oversight generally makes many patients willing to share data for research. So your goal is worthy and you should keep pursuing it. The next level ethical question becomes, if your dataset generates a successful clinically validated model to detect adverse events, will you patent and then release into open domain or commercialize it. If you commercialize it, will you share it back with your research participants in anyway? What is the right thing to do? These are all grey areas and one that informatician ethicists need to talk about openly. My 2 cents!
mohn 8y ago
I agree that AI has potential on the scanner. My academic research uses HeartVista's RTHawk software, which is essentially a driver to enable real-time MR imaging on magnets where the original manufacturer's pulse sequence API doesn't offer good real-time scanning options. I don't use it for its intended purpose of cardiac imaging, but apparently their latest version takes an AI approach to the problem of locating the heart within the field of view, determining its orientation, and prescribing imaging planes through the heart so all the important views that a radiologist would want can be acquired quickly. GE might even be on the way to integrating some AI into their scanner tech stack. As of version DV26 you have to specify the anatomical location when you start scanning, and it inserts a SAR scout sequence at the start of the protocol. The SAR scout is apparently looking for shapes matching the indicated anatomy, and if it doesn't find them (say, you're scanning a water-filled phantom that's not shaped like the head/brain you specified) it complains that the SAR estimate won't be as good as it could be. I don't know how they've implemented it, GE might just be using some simpler computer vision for this, but it's the sort of problem that could be well served by AI.
- rbobby 8y ago
  > their latest version takes an AI approach to the problem of locating the heart within the field of view, determining its orientation, and prescribing imaging planes through the heart so all the important views that a radiologist would want can be acquired quickly. So... autofocus for cardiac MRI's... :)
mentos 8y ago
If the price and size of an MRI machine could be brought down to that of a tanning bed, how might you see having one in every home improve health care?
- ixf 8y ago
  There are practical issues there. Liquid helium is relatively expensive and scarce, magnetic fields from the machine by definition need to be high to get good results, and to throw more fun into the mix you need to stop external radio interference from getting at the machine. Could you get the cost down to "specialised doctor's office" levels? Maaaaybe. Does AI have a role to play in that? Not one bit.
  - hhmc 8y ago
    Are there alternative fluids to liquid helium that could be used for cooling the magnets?
    - sxg 8y ago
      Liquid nitrogen is one alternative. Some further work is being done on room temperature superconductors, which obviates the need for any kind of cooling.
- joshgel 8y ago
  This is a common misconception I see in my patients all the time. Tests aren’t perfect and human bodies aren’t perfect. Even if a test has 99% specificity for a condition, if less than 1% of people getting the test has the condition at the time of the test, there will be more false positives than true positives. False positives require further investigations which have higher risks (incl death) just like true positives. Likewise, tests may show something that is indeed there, a mass for example, but that would never cause a clinically significant impact (the patient would otherwise never know they had it and it wouldn’t hurt their health). But that may still then lead to further investigations, which may be more invasive (read risk of death and morbidity) or at least anxiety in patients about what is going on with them. This is a long way of saying, it would be bad to test everyone with an MRI machine, let alone repeatedly. (It would be great if MRI costs were cheaper however).
VikingCoder 8y ago
As a resident, you should know that if you think it's appropriate for treatment, you basically have free rein to do what you want to with the MR data. If someone has made a free ML/AI tool, you can use it. What you're worried about is valid - is there a business model? And there doesn't need to be, for it to make sense. Research hospitals could be funding people to spend time developing new ML/AI algorithms, and then releasing them for free for people like you to use. More's the point, every country with socialized healthcare could be doing this, too. The FDA may indeed be making it impossible to make a profit from a business developing ML/AI, but that doesn't mean we shouldn't find a way to do it, not if it actually improves patient outcomes.
- toomuchtodo 8y ago
  > More's the point, every country with socialized healthcare could be doing this, too. More to the point, every country with socialized healthcare should be collaborating on software, algorithms, and "AI" models to that help everyone deliver better care more efficiently. Each dollar, euro, etc goes so much further when everyone can build off of each other's work.
  - VikingCoder 8y ago
    I'm kind of stunned we don't have more medical non-profits here in the US, developing healthcare software and giving it away for free.

dontreact 8y ago

I think you’re taking this viewpoint quite prematurely. It’s been about 3 years since we found architectures that surpass human level performance. The process in medicine is slow. FDA, billing codes etc. Give it 3 more years before drawing strong conclusions like this.

hef19898 8y ago
It might be a strong conclusion, but a reasonable and qualified one. The technical side of ML/AI does not change the main point, sales, a single. Because even in perfect scenario with a perfect AI/ML product to sell you still need a channel to customers. In this case doctors and hospitals. And from that perspective, considering the trend to full-service solutions for expensive equipment, the manufacturers of scanners are in a much better position to serve the needs of their customers. Good news for ML in general, not so good for all the start-ups out there. But then I have the same doubt regarding the majority of logistics, supply chain and mobility start-ups right now.
- dontreact 8y ago
  I disagree that the level of performance will not impact the sales picture. The technical side matters a lot for sales. If an AI product is associated with a billing code, that will hugely change the sales dynamic. However this is a high bar to clear in terms of performance. If the algorithms are worse than human level performance then I agree with the assessment. If they are above human level performance, I think the sales picture changes a lot. However this process will happen slowly since it will take time for regulatory and medical community to trust that a particular system truly and robustly outperforms humans.
  - hef19898 8y ago
    This are ver valid points, and I agree with that. You added tue nuance my post was missing.

sna1l 8y ago

It seems like reducing the cost/making MRIs more comfortable would be much more useful. Presumably if the machines didn't cost 3-5 million, with huge energy requirements, etc, you could get scanned a lot more often which probably be better than just using AI/ML? If you were able to scan cancer patients cheaply and quickly for a much lower cost and faster, I'd assume that would have a significant impact.

FireBeyond 8y ago
MRIs are typically (from my perspective working in the health insurance industry) profit centers for those who own them. Which leads to perverse incentives, like MRI manufacturers assisting physicians with setting up imaging consortiums, promising recoupment and profits within 18 months. Perhaps unsurprisingly, such doctors order imaging notably more often than others. Low field MRI machines are around $1M. $3M gets you a brand new, state of the art 3 tesla machine.
- mtgx 8y ago
  Sounds like an obvious "disruption strategy" for a startup here. Why hasn't anyone tried that yet?
  - frozenport 8y ago
    Lol what? Guy just told you the buisness model is making doctors prescribe more treatment than necessary. What are you going to disturpt? Doctors?
  - Aeolos 8y ago
    Patents and huge up-front expenses to create, certify, market and distribute such a device.
  - jayess 8y ago
    Many states limit supply of MRI machines through a "certificate of need" program where you have to convince a regulatory body that you should be allowed to own one.

napban 8y ago

I'm just starting out in a medical career, but keen to pursue a career in Radiology. I'm curious about your background with a computer science degree. Have you found opportunities to make use of your interests in relation to Radiology? My knowledge with computing is just limited to messing around with Linux, but I'm keen to learn more (for fun as well as career development). Are there any pathways you would recommend as high-yield for combining with a career in Radiology? My primary motivation is just enjoying tech, but it would be nice to develop my skills in a direction that allows me to incorporate an element of computing into my future work (whether that be side projects, academic research, or just making me more productive).

npunt 8y ago

This makes some sense both on tech and sales sides. Tech-wise, my guess is the benefits of AI/ML are best exploited at scan time with a scanner integration, rather than after the fact. Specifically, if the algorithm picks up something it can immediately dive in for a closer look while the patient is still there, shortening the turnaround time by weeks. There's also the opportunity to co-develop / tune AI/ML to specific types of scanners. Sales-wise, selling scanners is already a thing, and you don't have to create a new sales channel or figure out how to get buy-in. If a scanner works faster or better than others, hospitals already have a way to understand that through their procurement processes. And you may gain a higher margin by bundling AI/ML reading with hardware. Is this roughly what you see?

thomasfedb 8y ago

Decent datasets are very hard to come by, and the political gymnastics required to create and release them is horrible. I'm keen to create a dataset of paediatric physiological data during anaesthesia to help with event detection/preemption but my professor thinks getting permission to do so is all but impossible.

YayamiOmate 8y ago
It's kinda funny to see how relatively easy is to strip people of their general privacy rights for invigilation but how much pushback is there for medical data and medical purposes. Of course everything can be misused, though I would think that improved healthcare is a much better sellingpoint than being physically hurt by some terrorist actor.
najarvg 8y ago
I empathize. Pediatric consenting presents challenges more accentuated from what we see in adult patients. Generally we have seen (US academic med centers and hem-onc context) that shifting the focus from baseline expectation of privacy to responsible privacy driven research under oversight generally makes many patients willing to share data for research. So your goal is worthy and you should keep pursuing it. The next level ethical question becomes, if your dataset generates a successful clinically validated model to detect adverse events, will you patent and then release into open domain or commercialize it. If you commercialize it, will you share it back with your research participants in anyway? What is the right thing to do? These are all grey areas and one that informatician ethicists need to talk about openly. My 2 cents!

mohn 8y ago

I agree that AI has potential on the scanner. My academic research uses HeartVista's RTHawk software, which is essentially a driver to enable real-time MR imaging on magnets where the original manufacturer's pulse sequence API doesn't offer good real-time scanning options. I don't use it for its intended purpose of cardiac imaging, but apparently their latest version takes an AI approach to the problem of locating the heart within the field of view, determining its orientation, and prescribing imaging planes through the heart so all the important views that a radiologist would want can be acquired quickly. GE might even be on the way to integrating some AI into their scanner tech stack. As of version DV26 you have to specify the anatomical location when you start scanning, and it inserts a SAR scout sequence at the start of the protocol. The SAR scout is apparently looking for shapes matching the indicated anatomy, and if it doesn't find them (say, you're scanning a water-filled phantom that's not shaped like the head/brain you specified) it complains that the SAR estimate won't be as good as it could be. I don't know how they've implemented it, GE might just be using some simpler computer vision for this, but it's the sort of problem that could be well served by AI.

rbobby 8y ago
> their latest version takes an AI approach to the problem of locating the heart within the field of view, determining its orientation, and prescribing imaging planes through the heart so all the important views that a radiologist would want can be acquired quickly. So... autofocus for cardiac MRI's... :)

mentos 8y ago

If the price and size of an MRI machine could be brought down to that of a tanning bed, how might you see having one in every home improve health care?

ixf 8y ago
There are practical issues there. Liquid helium is relatively expensive and scarce, magnetic fields from the machine by definition need to be high to get good results, and to throw more fun into the mix you need to stop external radio interference from getting at the machine. Could you get the cost down to "specialised doctor's office" levels? Maaaaybe. Does AI have a role to play in that? Not one bit.
- hhmc 8y ago
  Are there alternative fluids to liquid helium that could be used for cooling the magnets?
  - sxg 8y ago
    Liquid nitrogen is one alternative. Some further work is being done on room temperature superconductors, which obviates the need for any kind of cooling.
joshgel 8y ago
This is a common misconception I see in my patients all the time. Tests aren’t perfect and human bodies aren’t perfect. Even if a test has 99% specificity for a condition, if less than 1% of people getting the test has the condition at the time of the test, there will be more false positives than true positives. False positives require further investigations which have higher risks (incl death) just like true positives. Likewise, tests may show something that is indeed there, a mass for example, but that would never cause a clinically significant impact (the patient would otherwise never know they had it and it wouldn’t hurt their health). But that may still then lead to further investigations, which may be more invasive (read risk of death and morbidity) or at least anxiety in patients about what is going on with them. This is a long way of saying, it would be bad to test everyone with an MRI machine, let alone repeatedly. (It would be great if MRI costs were cheaper however).

VikingCoder 8y ago

As a resident, you should know that if you think it's appropriate for treatment, you basically have free rein to do what you want to with the MR data. If someone has made a free ML/AI tool, you can use it. What you're worried about is valid - is there a business model? And there doesn't need to be, for it to make sense. Research hospitals could be funding people to spend time developing new ML/AI algorithms, and then releasing them for free for people like you to use. More's the point, every country with socialized healthcare could be doing this, too. The FDA may indeed be making it impossible to make a profit from a business developing ML/AI, but that doesn't mean we shouldn't find a way to do it, not if it actually improves patient outcomes.

toomuchtodo 8y ago
> More's the point, every country with socialized healthcare could be doing this, too. More to the point, every country with socialized healthcare should be collaborating on software, algorithms, and "AI" models to that help everyone deliver better care more efficiently. Each dollar, euro, etc goes so much further when everyone can build off of each other's work.
- VikingCoder 8y ago
  I'm kind of stunned we don't have more medical non-profits here in the US, developing healthcare software and giving it away for free.