23 ms·

As MDs, I think it is very clear that all of us who understand even the slightest about computers and tech see that machine learning is the way to go. Medicine

• deleted 10y ago
  [deleted]
• dev1n 10y ago
  After a procedure (unrelated to my heart), the anesthesiologist overseeing me suggested I go see a cardiologist. They noticed some tell-tale signs of a specific heart disease while they were monitoring the EKG readouts. I'm happy to say that anesthesiologist made my life a hell of a lot better because of that suggestion. Not something I would have expected a machine to tell me after a procedure completely unrelated to my heart.
  • rifung 10y ago
    But with sufficient compute power, couldn't you just have the machine equivalents of a cardiologist, anesthesiologist, neurologist, etc all looking at your information at the same time? It seems easier to scale compute power than to scale doctors considering how long doctors take to train. Of course, being able to get a machine to a doctor's level is not easy!
  • newyankee 10y ago
    Why do you think so, if you have the right data with many different algorithms running on it (even the one you are not interested in) i am sure it will uncover those. I am not doubting the hunch your Doctor felt due to his expertise was useless, but with continuous data ingestion and analyses coupled with as granular as the features can get this can only improve In fact complicated algorithms with so many streams of data that are probably not directly shared by specialists until it is needed may uncover new things even before traditional Doctors spot it
    • jimbokun 10y ago
      Because the programmers building the anesthesiologist machine learning model probably didn't think to include that check in the model, as they don't have the appropriate training.
      • btian 10y ago
        And for some reason you don't think some programmers are building ML models to classify all diseases known to man kind?
  • monkmartinez 10y ago
    A paramedic could see the same things on the EKG. It doesn't take much training to see bad rhythms on the monitor.
  • autokad 10y ago
    a benefit to ML is that they can check for everything. equipment isn't here for that yet either, but I imagine it will be. I'm assuming the 'data' for your condition was apparently in the EKG, thus there is no reason in the world an ML shouldnt have picked that up. Where as with humans, maybe you got a tired, new, or bad anesthesiologist. if you said they made the determination by something other than the EKG, I would be more convinced the 'machine' would have missed it
• NegatioN 10y ago
  I quite rarely see people get flamed for providing a well-formulated opinion on HN, so I don't think you need to preface your piece with that. I mostly agree with your post, ML has great potential to augment and assist doctors in making the right calls. Paraphrasing Jeremy Howard, "Doctors will be skeptical of these tools coming to take over their jobs at first, but will learn to trust them more and more when they see the kind of predictions they make, thereby slowly but steadily leading to their adoption (as an enhancement or tool) in many areas."
• nextos 10y ago
  The problem with deep learning right now is that there's not a great deal of methods outputting a nice estimation of uncertainty in predictions. But this will become less of an issue as they eventually converge with Bayesian methods, or at least if probability is introduced in a more principled way.
  • tma-1 10y ago
    This might be a dumb question, but why not use the classification accuracy score as a measure of uncertainty?
    • nextos 10y ago
      That's a rough measure of the a priori uncertainty. But you want the uncertainty conditioned to the particular observations you have made. A ton more here: http://mlg.eng.cam.ac.uk/yarin/blog_2248.html http://mlg.eng.cam.ac.uk/yarin/blog_2248.html
    • laingc 10y ago
      It's not a dumb question at all. The classification accuracy and "uncertainty" are different, but the explanation depends on what you mean by uncertainty. Let me try and give one intuitive explanation; if others would like to chime in with something better, by all means. Let's suppose that you are classifying objects in images - say bananas and oranges, but it could be tumors or anything that you like. So we train a classifier to predict this, and we find that of 100 classifications on a hold-out set, we get 73 of them correct. You might, quite reasonably, interpret this to mean that if we randomly select a new image of either an orange or a banana, we will have a 0.73 probability of classifying it correctly. (There are actually some subtleties in this interpretation which I'm ignoring, but they aren't so important for the point I want to make.) Suppose, however, that we draw out an image that we want to feed into our classifier, and we look at it for a moment. Suppose further that this image contains an object that is long, thing, curved and yellow. We'd expect our classifier to classify it as a banana, and sure enough, it does. Now we draw out another image, except this one has an object that is long, but bent almost completely in a circle, and is more orange than yellow. Now, we might still expect our classifier to classify this as a banana, but should the classifier really be as certain about this prediction as it was about the previous one? Intuitively, I would say not. However, the overall classification accuracy remains unchanged, and so we can't say anything in particular about the certainty of this prediction. So uncertainty isn't just the proportion of your results that you classify correctly. Furthermore, it also isn't exactly equivalent to the class probability produced by your classifier, though I don't think this is the best forum for me to get into the details on that.
• dfabulich 10y ago
  > What will be lacking is the automation of data collection, because you seem to underestimate by far the technical, legal, and ethical difficulties in getting the appropriate feedback to make ML appliances efficient. I firmly believe in reinforcement learning, and as long as the feedback system will be insufficient, doctors will prevail, highly-paid jerks or not. We're already seeing a significant rise in the role of nurse practitioners at the front line of medicine. Today, they gather the data and hand it to an MD, so handing it off to an ML system would be straightforward.
  • rscho 10y ago
    You overestimate the data gathering capabilities of the medical system by a huge margin. Even in seemingly objective parameters, you will see: missing data, reporting details dependent on the gatherer, a substantial amount of inaccuracy, etc. etc. Plus, you are describing people who barely know how to use a web browser. And you should also take into account that people driving the system don't even see the value of expert, scientific educated consultancy in those matters. For example, I was just asked to perform "data mining" on a dataset of 150 observations, 400 variables, and ~20% missing data by a renown professor. He told me I was bound to find interesting things in view of his ~400 back-to-back t-tests. No, I am quite confident in that ML will really take off when data fed to those systems will be automatically gathered.
    • dfabulich 10y ago
      Ohhh, I thought you were saying that we'll always need doctors to gather the data, but you meant that the ML systems will suck until they get enough data, and they can only get enough data if the process can be automated, so we'll need doctors to do diagnoses until the ML systems stop sucking.
      • rscho 10y ago
        Yes, absolutely.
      • neeleshs 10y ago
• revelation 10y ago
  The difficulty is not "following the right lane", it's the huge vision problem. Analog computers can follow a lane perfectly fine. If your profession only relies on reading a bunch of discrete values from monitors, it's a prime candidate for automation regardless of the complex process that derives the values.
  • rscho 10y ago
    I think I do understand machine vision, since I just published a paper using it. If my figure-of-speech does not convince you, I encourage you to step foot in an operating room if you get the occasion. I guarantee 100% that you will be unable to implement a system as efficient as the attending doc. Because numbers are just part of the job. You already see systems advertised as more efficient than anesthesiologists. Until we see those systems tested in a real, usual OR setting (meaning, hopelessly chaotic), you should take those efficiency statements with a grain of salt.
• agumonkey 10y ago
  I'm not for death of jobs, but I'd love to have a tad more information, a tad sooner, rather than relying on luck with which doctor is experienced or not, or wait until the best specialists are available. If ML unleash a global increase in diagnostics for all MDs than it's even better.
• zdean 10y ago
  MDs also have the benefit of an artificial monopoly (vs factory workers) that I imagine will fight hard to keep its members employed. https://www.cato.org/publications/policy-analysis/medical-monopoly-protecting-consumers-or-limiting-competition https://www.cato.org/publications/policy-analysis/medical-mo...
  • abakker 10y ago
    Calling medical education and licensing a monopoly is pretty intellectually dishonest. To borrow the OP's analogy, that is like saying drivers with licenses have a monopoly on driving. Seems like a pretty strange argument. Certainly, the medical industry does not face the same competitive pressure from outside, but that is the nature of industry in general. Rather than calling medicine a monopoly, it is more accurate to accuse heal care providers and practitioners of colluding to ensure prices are high. Monopolies by definition cannot collude since there would be nobody to collude with. In the grand scheme of things, I believe medical costs are accurately priced and it is people's wages that are not adjusting correctly.
    • zdean 10y ago
      The AMA controls the requirements for licensing, the schools that can educate for the purpose of licensing, and the number of licenses that can be issued. Exactly what is intellectually dishonest about calling that a monopoly? http://www.economist.com/blogs/freeexchange/2007/09/a_spoonful_of_monopoly_helps_t http://www.economist.com/blogs/freeexchange/2007/09/a_spoonf...
    • frisco 10y ago
      > To borrow the OP's analogy, that is like saying drivers with licenses have a monopoly on driving. Not so, as the number of medical residents is de facto set by Congress (due to how the funding system works), thereby limiting the number of doctors in each specialty.
      • sangnoir 10y ago
        If local production capacity is too low, why not import them?
• delegate 10y ago
  > but we won't be seeing fully integrated, doctor-replacement systems for a long time. I see your point and agree - if you look at ML and computing in general as a tool useful within the current context of medicine. But I think the whole field of medicine (or a big part of it) may become obsolete - because the change will be driven by technology, not medicine. By monitoring people's vitals in real time - think wrist bands which can do blood tests (+ urine, sweat, sperm, etc), feed that real time data to ML algorithms, train it on billions of people and you can accurately tell ahead of time when a person is getting sick. Next day the drone brings the medicine. Doctors will still be involved of course, but their role will be mostly to confirm whatever the algorithm has decided.. So I think we'll be seeing a move to preventive medicine / real-time monitoring during the next decade or so and within our lifetime people might not be involved in medicine at all. That is, if we have peace and things go according to plan... Which is a long bet of course.
  • apathy 10y ago
    Nice theory but acute medical emergencies are often stochastic. Let me know if you get to the point where you can predict a pulmonary embolism in members of the general public with enough accuracy to dispatch an ambulance. Preventable conditions are often a combination of genes plus environment plus luck. Trouble is, the "luck" part dominates more often than we'd like. This is why preventive medicine is often accused of being tremendously arrogant. We've got a long ways to go, and it would help to focus on the highest marginal benefit items. (We were supposed to have flying cars, and all I got was the sum total of Hunan knowledge on my phone... not a bad trade, on balance)
• rdlecler1 10y ago
  If anything it could put more MDs to work as problems are identified at home and escalated to an MD when there is an issue.
• smrtinsert 10y ago
  I don't think anyone is eagerly awaiting it (unless they were horribly misdiagnosed which is sad reality), but there is an inevitability to it. It's not a matter of if, its a matter of when. Greed will be the impetus, and eventually quality catching up will be the nail in the coffin for traditional medicine.
  • apathy 10y ago
    You present this as binary: doctors OR ai. I propose that the doctors who use ai to make themselves damned near infallible (by catching the corner cases where the ai is poorly trained) will make out like bandits, just like top lawyers. The ABA is a monopoly, too, and legal cases are perfect fodder for RNNs. Yet good corporate lawyers still make money faster than they can count it. Meanwhile, shitty lawyers are out of a job. Lather, rinse, repeat, but with a million times more regulation and inertia.
    • notahacker 10y ago
      I'm pretty sure the kind of AI actually discussed in the article is only going to be a good thing for doctors - even the pretty mediocre ones - by sending them more work rather than less. Person checks funny looking mole on smartphone app, app with intentionally conservative algorithm says there's some risk it might be a melanoma, dermatologist gets to have a proper look at it in three dimensions (and a second opinion from the medical grade version of the ML app). Result: more people visit doctors over issues that never bothered them that much and the doctor gets assistance with their diagnosis. And of course some of those people that wouldn't have bothered visiting the doctor under the old system actually do turn out to have a melanoma and the early diagnosis significantly improves their survival chances.
• bluetwo 10y ago
  (In my opinion) Doctors have done a good job of protecting them selves from technological disruption by only allowing it to be used where it is profitable to them (billing) and not where it would threaten them (diagnosis). Even the concept of electronic medical records has been resisted, and is currently poorly implemented. The gov't had to literally bribe doctors to convert to electronic systems and most seemed to go out and get the least poorly built products on the market. I'm not trying to paint them as evil. Heck, even NASA scientists were suspicious of computers taking their jobs. I see this in other fields all the time. Seeing the potential and seeing the current state of affairs kind of makes me sad. I want to live in the world where a balance has been reached. Where my medical record is a salient form of AI that checks if I lost those 10 pounds I promised and loops in the doctor when my flu symptoms linger too long. I want it to eliminate the hassle for doctors, hospitals, insurance companies as well as patients, and I think in the process it can drive costs down and raise quality of life.
  • jrowley 10y ago
    Doctors aren't the ones making these decisions - hospital administrators generally are choosing what to invest in. Most MDs I know are excited about research and not necessarily afraid entertaining some amount of change.
    • gnaritas 10y ago
      > Doctors aren't the ones making these decisions - hospital administrators generally are choosing what to invest in. Most doctors don't work in hospitals, they work in family practices and most definitely are making the decisions about how their practices operate. Most of us don't go to hospitals to see our doctors, we go our doctors private office.
      • jrowley 10y ago
        You're right - I was thinking about HMOs where care is very systemically administered. I think we'll see players like Kaiser introduce these tools before smaller private offices. They have more data than most other networks, and more resources to invest in R&D.
• danso 10y ago
  I hope computational thought somehow makes it into a MD's curriculum. It always depresses me when people see automation as a zero sum game against humans, instead of seeing automation as something to empower human practitioners.
• scarmig 10y ago
  My issue with doctors: Recently, my dad was sick with a pretty bad cough. Like, so bad that he couldn't speak without coughing. He fainted twice from minute long coughing fits, one of those times hitting his head his head on the stove on the way down, leaving a deep cut and blood everywhere. He went to at least three different doctors. He got a scan of his chest. Everything looked clear, and all of the doctors were stumped. Things were pretty bad. I mentioned this to a UCSF resident friend, and her immediate response was "Oh, is he on <some blood pressure medication I forget the name of>?" I was like, uh, let me see. Called my mom, she checked, and, lo and behold, he was on it. So his doctors took him off it and within a week he was better. This coughing wasn't some obscure side effect of the medication she knew through sheer brilliance: it's a side effect that's been widely known since the 1970's. Hell, it was on the drug's Wikipedia page. So there's a couple morals you could take from this. One would be, wow, doctors are smart to be able to diagnose an issue based on a single symptom and some reasonable assumptions about a patient's background! The other is that the median doctor is pretty worthless; spending tens of thousands of dollars gives you no guarantee you'll see someone competent; and that a medical system that relies on you grabbing drinks with a UCSF resident to get good results is fundamentally broken. Machine learning and expert systems don't have to be as awesome as the best doctors to be valuable. They don't need to be better than competent doctors, even. They just need to provide a bare level of competence to provide a huge amount of value.
  • cdelsolar 10y ago
    Atenolol? I'm not a doctor but I'm reasonably sure it's this.
    • fifteenforty 10y ago
      Not this. ACE inhibitors tend to cause a cough. You tend to get this side effect pretty quickly. It doesn't just occur randomly months or years after starting the drugs unless of course something else changes in your health.
  • inopinatus 10y ago
    You didn't say whether the medication was declared at the initial admission. Nonetheless the thing I took away most from your remark is a reminder to be aware of side-effects. Or more broadly, a reminder that patients are participants in their own treatment, and that the existence of doctors doesn't excuse us from responsibility toward ourselves & those we care for.
• throwaway729 10y ago
  Anesthesiology is one of those things that you'd think even classical control theory would be able to do given enough effort. You'd think... but not so! Apparently jobs that people go to med school to learn how to do require tremendous amounts of effort to automate. Who would've thought? ;-)
  • ZoeZoeBee 10y ago
    Anesthesiology is one of those things that have already been automated, even if you're unaware. The problem with anesthesia via robot is not a technical one at this point, rather it is an example of the current practitioners doing all that they can to preserve their way of life. https://www.technologyreview.com/s/601141/automated-anesthesiologist-suffers-a-painful-defeat/ https://www.technologyreview.com/s/601141/automated-anesthes... https://www.washingtonpost.com/business/economy/new-machine-could-one-day-replace-anesthesiologists/2015/05/11/92e8a42c-f424-11e4-b2f3-af5479e6bbdd_story.html?utm_term=.95cb71e6a3ab https://www.washingtonpost.com/business/economy/new-machine-...
    • Peradine 10y ago
      That robot performs sedation, not general anaesthesia. Sedation provides a slight depression in awareness and pain sensation, and is much easier than full general anaesthesia, in which the patient is completely paralysed, unconscious, and insensate. General Anaesthesia generally requires intubation, a complex practical procedure which can go wrong very quickly, and kill people very quickly. It requires close monitoring of numerous parameters, some of which are digital measures (blood pressure, heart rate, etc) but others are quite subjective, such as the patient's appearance and the current stage of the surgical procedure. The claim that this device is a replacement for an anaesthatist is similar to claiming that an automated wheel balancing machine will one day replace car mechanics. Certainly it can perform one specific component of one kind of anaesthesia, but it is far cry from the full skill set of an anaesthatist.
      • throwaway729 10y ago
        Exactly, thanks. Once you get to general, for example, the control problem is a lot more difficult because of the required precision.
• nickpsecurity 10y ago
  For a counterpoint, see the answers on this Quora: https://www.quora.com/Why-is-machine-learning-not-more-widely-used-for-medical-diagnosis https://www.quora.com/Why-is-machine-learning-not-more-widel... Medical diagnosis in the general case, esp with mis- or disinformation from patients, is quite complex. The data sets available aren't that good given the built-in biases & missing data. What we're seeing is deep learning can help when it focuses on one, little thing with a ton of good data available while ignoring everything else. That's what MYCIN did back when this concept started. That's not enough to replace MD's any time soon. What you'll find is we can at best supplement the decision-making practices of MD's by running their data through a bunch of ML systems in parallel to try to suggest things they might miss. This data will overtime feed into the ML systems to improve them. Augmented Intelligence, not Artificial Intelligence, will remain the best way to do things due to all the stuff in doctors' brains from their professional experience that's not in machine learning datasets.
  • shamino 10y ago
    I was about to comment about this topic, but you said everything I wanted to! Have an up vote!
  • BaronSamedi 10y ago
    One of the things the old expert systems like MYCIN could do was answer the question "Why", as in, why did you come to that conclusion? And it would show its reasoning. I may be mistaken but I don't think that the new, neural net based systems can do that. Interesting regression if true.
    • nickpsecurity 10y ago
      That was a problem in the early days. Expert systems could support root-cause analysis or justify themselves whereas neural nets couldn't. The new things are close to neural nets in operation. I'm doubting they can do it by default given that. Be interesting to see if anything is developed along those lines given work such as visualization of various layers of deep learning in pattern recognition.
• adamsbriscoe 10y ago
  Pretty soon, what happened to anesthesiology (one physician managing multiple extenders managing lots of technology in multiple places) is going to happen to the rest of medicine. Physicians will adapt by carving out even narrower niches ("I only specialize in the LEFT eye..." ;). But I really don't see a they-took-our-jobs moment until people are allowed to file lawsuits against AI. Companies will never put out an AI M.D. in the wild unless there's a flesh and blood counterpart to shoulder the liability (+1 job right there). Don't get me wrong though, I eagerly anticipate the day when going to the doctor/machine is not such a miserable soul-sucking experience... (I'm a physician.)
  • pokemon-trainer 10y ago
    I hate all physicians, except the one who saved my life.
• deleted 10y ago
  [deleted]
• ta_donk_gt 10y ago
  In my opinion, the AMA and the FDA are the main blockers of machines replacing doctors (outside of surgery). Nurses can do, and to a large extent already are doing the majority of the data collection. Beyond that, the doctor's main differentiable skill is pattern-matching and decision making based on experience. Machines with mountains of data generally perform this function much better than humans. That said, I do agree that we likely won't see the full potential of replacing doctors with machines in the near term simply due to the political and regulatory hurdles, as well as the need to overcome the fear of the public and address the very real and significant privacy issues. As to anesthesiology, I've actually done some work for a startup in that space working on a system that could very easily move anesthesiologists to a more supervisory role where they would watch (say) 50 surgeries at once (surgeries being handled by software tied into all monitors, as well as EMR systems for history and physical data, and able to dispense chemicals as needed) and step in if and when there was a problem. Technically, there is not much really stopping it, but politics and regulations present significant impediments (and probably rightly so, for now).
• slv77 10y ago
  The majority of anesthesia is routine sedation of healthy people for routine things like colon screenings. Those types of procedures are ripe for automation with systems like J&J's Sedasys cutting costs from $2000 to $200 a procedure. It was pulled off the market last year due to anesthesiologist opposition rather than problems with they system. It seems that the barriers to automation may be more the result of strong professional associations rather than specific complexities of the job. Thoughts?
• oddstorms 10y ago
  Actually, machines will never replace human judgment. It's absurd to even think machines are capable of such a thing. Machines are tools for humans to use. If your job is adding numbers or stacking boxes or something, sure. But anything beyond the basics is science fiction or delusion. A machine will never even approach an understanding of psychic continuity, for example. Now, I'm absolutely not saying that we can't engineer solutions in the medical field. You know more than I do about what diagnostic evaluation takes and how procedures are performed, so I don't pretend to understand that aspect perfectly. What I do know for sure is that a machine cannot and will never replicate human thought and decision making and cannot replace a doctor ever until the end of time. Also, you bring up a good point about salaries. Doctors are important and do great work but deserve to make no more than double or triple what the lowest paid person in their society makes. It's time to bring lawyers, doctors, accountants, developers, engineers—the professional class—back down to reality with the rest of us.
  • sAvi0r 10y ago
    i honestly can't tell if this comment is a parody of something/copypasta or not tbh
    • cing 10y ago
      Agreed. Reads like an AI trying a bit too hard to appear human. Charged with emotion, arrogance, lacking reasoning.
• Moshe_Silnorin 10y ago
  Yes, you are safe because of licensure and regulatory capture. Hardly seems fair to the factory workers.
• qwrusz 10y ago
  Don't worry Doc, your job is safe. Machines replacing high-touch specialized professions like doctors is not the risk here. The bigger immediate risk may be from machines making these jobs much much shittier, and then there's fallout. You won't get fired, but you may want to quit. MDs are not factory workers. First you have the AMA protecting you. Second, there appears to be a very strong preference by humans for medical care to involve another human being there providing the care - in person. There are other professions where machines are already much better than humans and the need for humans to even be there in person is debatable. Airline pilots for example. Of course, while a computer can fly a plane better than a human and planes can be flown remotely, it will take much longer for passengers to accept the idea and get on a plane without a human pilot in the cockpit. The effect of machines for pilots already highlights risks to come. Humans still need to be there in person, but they almost never need to do anything but sit there. The job is to be a warm body and tell people to look out the window while they fly over the Rockies (seriously, take off to landing no human is really needed to fly anymore - pilots do nothing 95% of the time). How did machines taking over the cockpit affect how the pay, benefits, competency and job satisfaction of pilots took a nosedive? Did you see the movie "Sully"? Where a human did step in over the machine, he almost got crucified even though it was the right move he only just barely was able to convince others of it. Is it possible machines won't replace doctors very soon but could soon start to lead to lower pay, less trust, less prestige (here come the nurse practitioners at least), less need to use your brains at work and less meaningful interaction with patients...? And when a machine can't do something in those rare cases, will the doctor be ready for that? Think the best and brightest still will want to do this? Doctors already are not fans of that thing where patients come in having looked up their symptoms online, well they are about to do that 10x and be more right than you. Total guess here: how likely is it that we see the best and brightest increasingly go into medical research instead of practice medicine? As the corporate pharma kickbacks you guys get can't make up for the low pay and shitty shit job conditions machines have created for doctors, while nurses and B-team quality doctors take over the actual physician working with patients stuff?