11 ms·

I'm an interventional radiologist with a master's in computer science. People outside radiology don't get why AI hasn't taken over. Can AI read diagnostic imag

• cogman10 1y ago
  Doesn't most of the stuff a radiologist does get double checked anyways by the doctor that orders the scan in the first place? I guess not a more typical screening scan like a mammogram. However, for anything else like a CT, MRI, Xray, etc. I expect the doctor/NP that ordered it in the first place will want to take a look at the image itself and not just the report on the image.
  • nutjob2 1y ago
    A primary physician (or NP) isn't in a position to validate the judgement of a specialist. Even if they had the training and skill (doubtful), responsibility goes up, not down. It's all a question of who is liable when things go wrong.
  • Spooky23 1y ago
    Not meaningfully. Beyond basics like a large tumor, a bone break, etc, there’s alot too it.
    • coderatlarge 1y ago
      my pcp doesn’t even have the tools to view an mri even though part of a hospital system.
      • Spooky23 1y ago
        That’s an issue with that practice. I had the tools to view MRIs in my laptop.
        • coderatlarge 1y ago
          that’s heartening. do you believe the average pcp is competent to review an mri and act on it given the specialist’s report?
          • coderatlarge 1y ago
            also note the hospital system is extremely paranoid about data management and probably wouldn’t allow a pcp to have mri data on a laptop. even specialists seem to only review mri on hospital desktops.
  • n8henrie 1y ago
    As an ER doc I look at a lot of my own studies, because I'm often using my interpretation to guide real-time management (making decisions that can't wait for a radiologist). I've gotten much better over time, and I would speculate that I'm one of the better doctors in my small hospital at reading my own X-rays, CTs, and ultrasounds. I am nowhere near as good as our worst radiologist (who is, frankly... not great). It's not even close.
    • sharkweek 1y ago
      I’m fascinated. What makes a great radiologist so much better than the average?
      • incone123 1y ago
        Calling the edge cases correctly, I would think. I hurt my arm a while back and the ER guy didn't spot the radial head fracture, but the specialist did. No big deal since the treatment was the same either way.
      • 71bw 1y ago
        You're specifically trained to look at the scans, and not to do 75 other things as well, only to use scans to aid your whatever you're doing.
      • lostlogin 1y ago
        Im not the OP and I’m an MR tech. I rate techs against non-radiology trained physicians in terms of identifying pathology. However techs aren’t anywhere near the ability of a radiologist. Persuading junior techs not to scan each other and decide the diagnosis is a reoccurring problem, and it comes up too often. These techs are trained and are good. I have too many stories about things techs have missed which a radiologist has immediately spotted.
    • seesthruya 1y ago
      As a working diagnostic radiologist in a busy private practice serving several hospitals, this has been my experience as well. We have some excellent ER physicians, and several who are very good at looking at their own xrays. They also have the benefit of directly examining the patient, "it hurts HERE", while I am in my basement. Several times a year they catch something I miss! But when it comes to the hard stuff, and particularly cross-sectional imaging, they are simply not trained for it.
• deleted 1y ago
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• newyankee 1y ago
  But this indicates lack of incentives to reduce healthcare costs by optimisation. If AI can do something well enough , and AI + humans surpass humans leading to costs reductions/ increased throughput this should be reflected in the workflows. I feel that human processes have inertia and for lack of a better word, gatekeepers feel that new, novel approaches should be adopted slowly and which is why we are not seeing the impact, yet. Once a country with the right incentive structure (e.g. China ) can show that it can outperform and help improve the overall experience I am sure things will change. While 10 years progress is a lot in ML, AI , in more traditional fields it probably is a blip to change this institutional inertia which will change generation by generation. All that is needed is an external actor to take the risk and show a step change improvement. Having experienced how healthcare in US I feel people are only scared to take on bold challenges
  • numpad0 1y ago
    Or, maybe artifacts justify prices less so than amounts of souls bothered will. Robotic medical diagnosis could save costs, but it could suppress customers' appetite too, in which case, like you said, commercial healthcare providers would not be incentivized to offer it.
  • Spooky23 1y ago
    Remember, the AI doesn’t create anything, so you add risk potentially to the patient outcome and perhaps make advancement more difficult. My late wife had to have a stent placed in a vein in her brain to relieve cranial pressure. We had to travel to to New York for an interventional radiologist and team to fish a 7 inch stent and balloon from her thigh up. At the time, we had to travel to NYC, and the doctor was one of a half dozen who could do the procedure in the US. Who’s going to train the future physician the skills needed to develop the procedure? For stuff like this, I feel like AI is potentially going to erase certain human knowledge.
    • chii 1y ago
      > Who’s going to train the future physician the skills needed to develop the procedure? i would presume that AI taking over won't erase the physical work, which would mean existing training regimes will continue to exist. Until one day, an AI robot is capable of performing such a procedure, which would then mean the human job becomes obsolete. Like a horse-drawn coach driver - that "job" is gone today, but nobody misses it.
• mettamage 1y ago
  So you studied like 8 years of med school [1] and 2 years of CS? Damn! That’s a lot. [1] I don’t know the US system so it’s just a guess
  • aabajian 1y ago
    4 years undergrad (CS, math, bio) 4 years med school 2 years computer science 6 years of residency (intern year, 4 years of DR, 1 year of IR) 16 years...
    • arethuza 1y ago
      Why do you need the first 4 years undergrad - in places like the UK you can go straight to study medicine from secondary school at age ~18?
      • chromatin 1y ago
        The belief is -- and it is one that I share -- that this makes for more well rounded, human physicians. Additionally, a greater depth of thinking leads to better diagnosticians, and physician-scientists as well (IMO). Now, all of this is predicated on the traditional model of the University education, not the glorified jobs training program that it has slowly become.
        • hnfong 1y ago
          Cynically, it's also a way for the US system to gatekeep "poor" people from entering professions like medicine and law because of the extra tuition fees (and opportunity time-cost) needed to complete their studies.
          • chromatin 1y ago
            I am a natural skeptic, but in this case I think it is just an accident of history how different systems developed. FWIW, although this is not well known, many medical schools offer combined BA/MD degrees, ranging from 4-8 years: https://students-residents.aamc.org/medical-school-admission-requirements/medical-schools-offering-combined-baccalaureate-md-programs-state-and-program-length-2024-2025 https://students-residents.aamc.org/medical-school-admission... When I went 20 years ago, my school did not require a bachelor's degree and would admit exceptional students after 2 years of undergraduate coursework. However I think this has now gone away everywhere due to AAMC criteria
• doctorpangloss 1y ago
  > Unless the law changes... That's it? I don't know. Doesn't sound like a very big obstacle to me. But I don't think AI will replace radiologists even if there was a law that said like, "blah blah blah, automated reports, can't be sued, blah blah." I personally think the consulting work they do is really valuable and very difficult to automate, we would be in an AGI world where radiologists get replaced, which seems unlikely. The bigger picture is that we are pretty much obligated to treat people medically, which is a good thing, so there is a lot more interest in automating healthcare than say, law, where spending isn't really compulsory.
  • Muromec 1y ago
    > I don't know. Doesn't sound like a very big obstacle to me A lot of things are one law amendment away from happening and they aren’t happening. This could well become another mask mandate, which while being reasonable in itself, rubs people wrong way just enough to become a sacred issue.
    • marcosdumay 1y ago
      Very few things the general public wants stays just one law amendment away for long. And almost all of those things are for the benefit of powerful people.
    • T-800Rad 1y ago
      I think you're right, and the source of the change of legislation may well be related to Medicare and Medicaid cost cutting. After all, it's difficult to see the federal government.
• smrtinsert 1y ago
  At some point medical equipment is certified in some way for use. Could the same happen for imaging AIs?
  • speakfreely 1y ago
    But the equipment is operated by a person, and the diagnostic report has to be signed off by a person, who has a malpractice insurance policy for personal injury attorneys to go after. The system is designed a nanny-state fashion: there's no way to release practitioners from liability in exchange for less expensive treatments. I doubt this will change until healthcare pricing hits an extremely expensive breaking point.
  • scheme271 1y ago
    The article mentions a system for diabetic retinopathy diagnosis that is certified and has liability coverage. It sounds like it's the only one where that occurs. For everything else, malpractice insurance explicitly excludes any AI assisted diagnosis.
    • epcoa 1y ago
      Malpractice insurance tends to exclude the diabetic retinopathy one too.. the vendor has to provide insurance.
• scythe 1y ago
  I'm moderately amused that as an interventional radiologist, you didn't bother to mention that IRs do actual procedures and don't just WFH. When I was doing my DxMP residency there was a joke among the radiology residents that IRs had slotted into the cushiest field of medicine and then flopped the landing by choosing the only subfield that requires physical work.
  • aabajian 1y ago
    Well I do enjoy procedures. As for diagnostics, it’s very different when you come from a CS background. On a basic level, software exists to expedite repetitive human tasks. Diagnostic radiology is an extremely repetitive human task. When I read diagnostics, there’s a voice in the back of my head saying, “I should be writing code to automate this rather than dictating it myself.”
• epcoa 1y ago
  For real though how close are we to a product that takes an order for an ED or inpatient CT A/P, protocols it then reads the images and can read the chart and spits out a dictated report without any human intervention that ends up usable as is even 90% of the time.
  • layoric 1y ago
    Right, the last 10% will be expensive or you accept a potential 10% failure rate.
    • epcoa 1y ago
      Maybe I should have said 5%. 90% was a made up threshold. How close are we to even a basic “level 5”, ED doc puts in order for indication: “concern for sepsis, lol”, rad tech does their thing and a finished read appears, with no additional human involved except for maybe a review but not even 50% of the time is any addendum needed.
  • seesthruya 1y ago
    We are not close at all.
• kbos87 1y ago
  This is like saying that self-driving cars won't ever become a thing because someone behind the wheel needs to be to blame. The article cites AI systems that the FDA already has cleared to operate without a physicians' validation.
  • CSSer 1y ago
    I'm curious how many people would want a second opinion (from a human) if they're presented with a bad discovery from a radiological exam and are then told it was fully automated. I have to admit if my life were on the line I might be that Karen.
    • captainkrtek 1y ago
      Id be more concerned about the false negative. My report says nothing found? Sounds great, do I bother getting a 2nd opinion?
      • jayknight 1y ago
        You pay extra for a doctor's opinion. Probably not covered by insurance.
        • ares623 1y ago
          That's horrific. You pay insurance to have ChatGPT make the diagnosis. But you still need to pay out of pocket anyway. Because of that, I am 100% confident this will become reality. It is too good to pass up.
          • CSSer 1y ago
            I mean, we already have deductibles and out-of-pocket maximums. If anything, this kind of policy could align with that because it's prophylactic. We can ensure we maximize the amount we retrieve from you before care kicks in this way. Yeah, it tracks.
          • 1y ago
• OptionOfT 1y ago
  Is there a risk that radiologists miss stuff because they get a pre-written report by AI that pushes them in a certain direction?
  • thyristan 1y ago
    Maybe, but there is already that risk of some influence from other doctors, patients, nurses and general circumstances. When an X-Ray is ordered, there is usually a suspected diagnosis in the order like "suspect sprain, pls exclude fracture", "suspect lung cancer". Patients will complain about symptoms or give the impression of a certain illness. Things like that already place a bias on the evaluation a radiologist does, but they are trained to look past that and be objective. No idea how often they succeed.
• Wololooo 1y ago
  Did the need raise through the use of silicon X ray detectors that improved the handling of images and reduced the time needed to get done imaging meaning that it made it faster, cheaper and less cumbersome, increasing the number of requests for X ray imaging?
• teleforce 1y ago
  >People outside radiology don't get why AI hasn't taken over AI will probably never taking over, what we really need is AI working in tandem with radiologist and complementing their work to help with their busy schedule (or limited number of radiologist). The OP title can also be changed to "Demand for human cardiologist is at an all-time high", and is still be true. For example in CVDs detection cardiologist need to diagnose the patient properly, and if the patient not happy with the diagnostic he can get a second opinion from another cardiologist, but cardiologist number is very limited even more limited than radiologist. For most of the countries in the world, only several hundreds to several thousands registered cardiologist per country, making the ratio about 1:100,000 cardiologist to population ratio. People expecting cardiologist to go through their ECG readings but do you know that reading ECG is very cumbersome. Let's say you have 5 minutes ECG signals for the minimum requirement for AFib detection as per guideline. The standard ECG is 12-lead resulting in 12 x 5 x 60 = 3600 beats even for the minimum 5 minutes durations requirements (assuming 1 minute ECG equals to 60 beats). Then of course we have Holter ECG with typical 24-hour readings that increase the duration considerably and that's why almost all Holter reading now is automated. But current ECG automated detection has very low accuracy because their accuracy of their detection methods (statistics/AI/ML) are bounded by the beat detection algorithm for example the venerable Pan-Tompkins for the fiducial time-domain approach [1]. The cardiologist will rather spent their time for more interesting activities like teaching future cardiologists, performing expensive procedures like ICD or pacemaker, or having their once in a blue moon holidays instead of reading monotonous patients' ECGs. I think this is why ECG reading automation with AI/ML is necessary to complement the cardiologist but the trick is to increase the sensitivity part of the accuracy to very high value preferably 100% so the missing potential patients is minimized for the expert and cardiologist in the loop exercise. [1] Pan–Tompkins algorithm: https://en.wikipedia.org/wiki/Pan%E2%80%93Tompkins_algorithm https://en.wikipedia.org/wiki/Pan%E2%80%93Tompkins_algorithm
  • eMPee584 1y ago
    As in.. for small durations of "never" ? ..
  • the_real_cher 1y ago
    This seems like a task an A.I. would be really good at or even just a standard algorithm.
• wiz21c 1y ago
  Provided enough political will (and you know that this can be correlated to many factors, like lobbying), laws can be changed.
• seesthruya 1y ago
  I'm a diagnostic radiologist with 20 years clinical experience, and I have been programming computers since 1979. I need to challenge one of your core assumptions. > Can AI read diagnostic images better than a radiologist? Almost certainly the answer is (or will be) yes. I'm sorry, but I disagree, and I think you are making a wild assumption here. I am up to date on the latest AI products in radiology, use several of the, and none of them are even in the ballpark on this. That vast majority are non-contributory. It is my strong belief that there is an almost infinite variation in both human anatomy and pathology. Given this variation, I believe that in order for your above assumption to be correct, the development of "AGI" will need to happen. When I interpret a study I am not just matching patterns of pixels on the screen with my memory. I am thinking, puzzling, gathering and synthesizing new information. Every day I see something I have never seen before, and maybe no one has ever seen before. Things that can't and don't exist in a training data set. I'm on the back end of my career now and I am financially secure. I mention that because people will assume I'm a greedy and ignorant Luddite doctor trying to protect my way of life. On the contrary, if someone developed a good replacement for what I don, I would gladly lay down my microphone and move on. But I don't think we are there yet, in fact I don't think we're even close.
  • sokoloff 1y ago
    Can a human reliably carefully study for hours on end imaging from screening tests (think of a future world where whole-body MRI scanning for asymptomatic people becomes affordable and routine thanks to AI processing) and not miss subtle anomalies? I can easily imagine that humans are better at really digging deeply and reasoning carefully about anomalies that they notice. I doubt they're nearly as good as computers at detecting subtle changes on screens where 99% of images have nothing worrisome and the priors are "nothing is suspicious". I don't want to equate radiologists with TSA screeners, but the false negative rate for TSA screening of carryon bags is incredibly high. I think there's an analog here about the ability of humans to maintain sustained focus on tedious tasks.
    • bonsai_spool 1y ago
      > Can a human reliably carefully study for hours on end imaging from screening tests This is actually very common in radiology where some positions have shifts of 8-12 hours, where one isn't done until all the studies on the list have been read. > think of a future world where whole-body MRI scanning for asymptomatic people becomes affordable and routine thanks to AI processing) and not miss subtle anomalies? The bottleneck in MRI is not reading but instead the very long acquisition times paired with the unavailability of the expensive machinery. If we charitably assume that you're thinking of CT scans, some studies on indiscriminate imaging indicate that most findings will be false positives: https://pmc.ncbi.nlm.nih.gov/articles/PMC6850647/ https://pmc.ncbi.nlm.nih.gov/articles/PMC6850647/
• cyrillite 1y ago
  I am actively researching this friction and others like it. I would love it if you happened to have recommendations for literature that 3rd parties can use to corroborate your experience (I’ve found some, but this is harder to uncover than I expected as I’m not in the field)
• pgreenwood 1y ago
  Add to that that the demand for imaging is not fixed. Even if somehow imaging became a lot cheaper to do with AI, then likely we would just get more imaging done instead of having fewer radiologists.
• Workaccount2 1y ago
  What about the patient that doesn't want to pay $6,000 to go from 99.9% accuracy to 99.95% accuracy?
  • newyankee 1y ago
    This is exactly the tradeoff that works in healthcare of poor countries, mostly because the alternative is no healthcare
  • hbd-investor 1y ago
    I think its the other way around AI would certainly have better accuracy than a human, AI can see things pixel by pixel. You can take a 4k photo of anything, change one pixel to pure white and a human wouldn't be able to find this pixel by looking at the picture with their eyes. A machine on the other hand would be able to do it immediately and effortlessly. Machine vision is literally superhuman, For example Military camo can easily fool human eyes. But a machine can see through it clear as day. Because they can tell the difference between Black Hex #000000 RGB 0, 0, 0 CMYK 0, 0, 0, 100 and Jet Black Hex #343434 RGB 52, 52, 52 CMYK 0, 0, 0, 80
  • ninetyninenine 1y ago
    You know the crazy thing about this? For this application I think it’s similar to spam. AI can easily be trained to be better than a human. And it’s definitely not a 0.05 percent difference. AI will perform better by a long shot. Two reasons for this. 1. The AI is trained on better data. If the radiologist makes a mistake that mistake is identified later and then the training data can be flagged. 2. No human indeterminism. AI doesn’t get stressed or tired. This alone even without 1. above will make AI beat humans. Let’s say 1. was applied but that only applies for consistent mistakes that humans make. Consistent mistakes are eventually flagged and shows up as a pattern in training data and the AI can learn it even though humans themselves never actually notice the pattern. Humans just know that the radiologists opinion was wrong because a different outcome happened, we don’t even have to know why it was wrong and many times we can’t know… just flagging the data is enough for the AI to ingest the pattern. Inconsistent mistakes comes from number 2. If humans make mistakes that are due to stress the training data reflecting those mistakes will be minuscule in size and also random without pattern. The average majority case of the training data will smooth these issues out and the model will remain consistent. Right? A marker that follows a certain pattern shows up 60 times in the data but one time it’s marked incorrectly because of human error… this will be smoothed out. Overall it will be a statistical anomaly that defies intuition. Similar to how flying in planes is safer than driving. ML models in radiology and spam will beat humans. I think we are under this delusion that all humans are better than ML but this is simply not true. You can thank LLMs for spreading this wrong intuition.
• missedthecue 1y ago
  So you're telling me the reason an extremely expensive yet totally redundant cost in the healthcare infrastructure will remain in place is because of regulatory capture? You're probably right.
• notmyjob 1y ago
  “Unless the law changes” Famous last words.
• deleted 1y ago
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• borroka 1y ago
  However, it is also because, in matters of life or death, as a diagnosis from a radiologist can be, we often seek a second opinion, perhaps even a third. But we don't ask a second opinion to an "algorithm", we want a person, in front of us, telling us what is going on. AI is and will be used in the foreseeable future as a tool by radiologists, but radiologists, at least for some more years, will keep their jobs.
• stavros 1y ago
  I'm not going to comment on whether AI is better than human radiologists or not, but if it is, what will happen is this: Radiologists will validate the results but either find themselves clicking "approve, approve, approve" all day, or disagree and find they were wrong (since our hypothesis is that the AI is better than a human). Eventually, this will be common knowledge in the field, hospitals will decide to save on costs and just skip the humans altogether, lobby, and get the law changed.
• T-800Rad 1y ago
  I used to think that too. AI can already do better at screening mammography than a radiologist with a lower miss rate. Given that, insurance rates to cover AI should be even lower than for a radiologist, lawsuits will happen, but with a smaller number of missed cases the number should go down. Paul Kedrosky had an interesting analogy when the automobile entered the scene. Teamsters (the men who drove teams of horses) benefited from rising salaries, even as new people declined to enter the "dead end" profession. We may well be seeing a similar phenomenon with Radiologists. Finally, I'd like to point out that rising salaries mean there are greater incentives to find alternative solutions to this rising cost. Given the erratic political situation, I will not be surprised to see a relatively sudden transition to AI interpretation for at least a minority of cases.