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?
Perhaps it is time to found the American Board of Computational Radiology (or Medicine)? There seems to be a chilling effect on tech innovation in the medical space in the US. On recent trips to the dentist, it seems like most of the cool new tech is coming out of Israel.
The radiologist can now work 10x faster and still bills the hospital the same amount.
The Doctor's Guild is exceedingly powerful.
I really wish Wallmart or Amazon would get into providing healthcare services on the long tail - a lot of common stuff.
I sounds odd but both those companies are built around ripping margins out of the value chain and not keeping much for themselves.
Ok, maybe not either of them ... but something like that: The 'Walmart of Healthcare' that revolutionizes cost.
Also - there are enough Medical Practitioners who would work there. Enough of them do care about patient outcomes, cost etc..
Strong disagree here. Lets put aside the math and focus on money.
I dont know much about seismic interpretation, but I know a lot about Radiology+CV/ML. I was CTO+CoFounder for three years full time of a venture-backed Radiology+CV/ML startup.
From what I can see, there is a huge conflict of interest w/r/t Radiology (and presumably any medical field) in the US. Radiologists make a lot of money -- and given their jobs are not tied to high CoL regions (as coders jobs are), they make even more on a CoL-adjust basis. Automating these jobs is the equivalent of killing the golden goose.
Further, Radiologists standards of practice are driven partly by their board (The American Board of Radiology) and the supply of labor is also controlled by them (The American Board of Radiology) by way of limited residency spots to train new radiologists.
So Radiologists (or any medical specialist) can essentially control the supply of labor, and control the standards of best practice, essentially allowing continued high salaries by way of artificial scarcity. WHY ON EARTH WOULD THEY WANT THEIR WORK AUTOMATED AWAY?
My experience during my startup was lots of radiologists mildly interested in CV/ML/AI, interested in lots of discussions, interested in paid advisory roles, interested in paid CMO figurehead-positions, but mostly dragging their feet and hindering real progress, presumably because of the threat it posed. Every action item was hindered by a variety of players in the ecosystem.
In fact, most of our R&D and testing was done overseas in a more friendly single payer system. I dont see how the US's fee-for-service model for Radiology is ever compatible with real progress to drive down costs or drive up volume/value.
Not surprisingly, we made a decision to mostly move on. You can see Enlitic (a competitor) didnt do well either despite the star-studded executive team. Another competitor (to be unnamed) appears to have shifted from models to just licensing data. Same for IBM/Merge.
Going back to seismic interpretation -- this cant be compared to Radiology from a follow-the-money perspective because seismic interpretation isnt effectively a cartel.
Happy to speak offline if anyone is curious about specific experiences. DM me.
As I posited, there is research interest and a few people doing it clinically. Your links support this. What they don't support is the idea that this is typical clinical practice.
https://twitter.com/BernardBendokMD/status/13785056756894556...
She had that too.
> This is why fMRI is often used as a planning step before awake cortical mapping during the actual surgery.
That must have been the case.
I guess surgeons were trying to do whatever was in their power to not damage her speech center. Right after operation she had a few brief seizures when she lost ability to speak for a minute or two, but as the damage healed they quickly stopped.
Fair enough, I didn't mean to suggest you were I was speaking more generally but worded that poorly.
My comments come from systems supporting thousands of clinical neurooncological procedures (i.e. tumor resections) in planning and execution with very little interest or utilization of fMRI beyond a handful proponents and their sites. Quite literally barely on the radar of most of the neurosurgeons apart from occasional papers, and some of them are quite negative about it also.
I could have an inaccurate picture of the breadth of clinical practice, and it's certainly a couple years out of date, but I would be very surprised to find a huge upsurge of usage outside research had happened.
It is certainly the case that the articles claim of "transformation" hasn't happened in that space.
If the article had instead claimed that some of the trickiest cases tend to have fMRI done (true, surgeons will take all they help they can get trying cases that otherwise might be inoperable) or that they are a feature of high profile academic sites (also mostly true) I wouldn't have objected.
This is not even close to true. The clinical impact of fMRI is very constrained. I've met many clinicians who have completely written it off at this point. Others that remain interested but find it mostly impractical and error prone. The only people I've met who seem to have any significant investment in it as a technology are cognitive scientists, and that's a ways from medicine.
> It allows non-invasive mapping of a patient’s brain regions to enable more accurate, precise neurosurgery,1"
Approximately nobody does this. fMRI isn't really even on the radar for most neurosurgeons. It's only recently that even detailed structural information (e.g. DTI) has got some real traction, let alone functional info. Note commercial vendors have had clinical packages on the scanners for (nearly? I forget who shipped DWI stuff first) a couple decades now. No such thing exists for fMRI, at minimum you need to buy a 3rd party processing system and may need a research key on your scanner.
Some researchers are interested in this; that's a long way from transforming anything.
> " as well as validating pharmacological effects of potential drugs on human brains.2"
There is perhaps a bit more promise here, but it's still way into the research only end. In the 15 years since the referenced paper was published, not much of this "promise" has been realized as far as I know (but this is further from my wheelhouse)
This is not the case, for example see the GE BrainWave software.
https://www.gehealthcare.com/products/advanced-visualization...
My experience with getting a sonogram was that the sonogram wasn't that expensive, but getting it read was hugely expensive. I understand that there are issues of liability, but it's really frustrating that I'm saddled with a high deductible healthcare plan where access to useful medical stuff is stuck behind 3-4 digit costs. Want antibiotics, inhalers, ADHD meds - all of which are pretty cheap in generic form? Pay $100 to the doctor for the privilege. People have very little agency in this system.
I guess at the end of the day I'd like to see open data (I'm able to get the images/data from all kinds of scans & diagnostics), and some kind of transparent system for submitting my data for diagnosis or analysis. There may be caveats & waivers, but I'd be willing to pay $10 to an AI service to tell me "You definitely need to consult with a radiologist based on the data presented" before I pay a radiologist orders of magnitude more to tell me that everything looks OK.